AdaColmap | | | 97.23 80 | 96.80 81 | 98.51 100 | 99.99 1 | 95.60 146 | 99.09 203 | 98.84 54 | 93.32 120 | 96.74 120 | 99.72 64 | 86.04 177 | 100.00 1 | 98.01 78 | 99.43 91 | 99.94 64 |
|
CNVR-MVS | | | 99.40 1 | 99.26 1 | 99.84 2 | 99.98 2 | 99.51 2 | 99.98 6 | 98.69 62 | 98.20 3 | 99.93 1 | 99.98 2 | 96.82 13 | 100.00 1 | 99.75 11 | 100.00 1 | 99.99 11 |
|
MCST-MVS | | | 99.32 3 | 99.14 3 | 99.86 1 | 99.97 3 | 99.59 1 | 99.97 12 | 98.64 69 | 98.47 2 | 99.13 54 | 99.92 5 | 96.38 22 | 100.00 1 | 99.74 13 | 100.00 1 | 100.00 1 |
|
mPP-MVS | | | 98.39 42 | 98.20 39 | 98.97 71 | 99.97 3 | 96.92 105 | 99.95 31 | 98.38 128 | 95.04 67 | 98.61 76 | 99.80 43 | 93.39 89 | 100.00 1 | 98.64 60 | 100.00 1 | 99.98 43 |
|
CPTT-MVS | | | 97.64 68 | 97.32 67 | 98.58 94 | 99.97 3 | 95.77 138 | 99.96 19 | 98.35 132 | 89.90 213 | 98.36 85 | 99.79 44 | 91.18 127 | 99.99 27 | 98.37 68 | 99.99 13 | 99.99 11 |
|
DP-MVS Recon | | | 98.41 40 | 98.02 46 | 99.56 15 | 99.97 3 | 98.70 33 | 99.92 52 | 98.44 106 | 92.06 168 | 98.40 84 | 99.84 34 | 95.68 32 | 100.00 1 | 98.19 70 | 99.71 72 | 99.97 53 |
|
PAPR | | | 98.52 33 | 98.16 41 | 99.58 14 | 99.97 3 | 98.77 25 | 99.95 31 | 98.43 111 | 95.35 62 | 98.03 96 | 99.75 60 | 94.03 75 | 99.98 31 | 98.11 74 | 99.83 61 | 99.99 11 |
|
HFP-MVS | | | 98.56 29 | 98.37 31 | 99.14 50 | 99.96 8 | 97.43 82 | 99.95 31 | 98.61 75 | 94.77 73 | 99.31 45 | 99.85 20 | 94.22 68 | 100.00 1 | 98.70 54 | 99.98 25 | 99.98 43 |
|
region2R | | | 98.54 31 | 98.37 31 | 99.05 64 | 99.96 8 | 97.18 96 | 99.96 19 | 98.55 87 | 94.87 71 | 99.45 35 | 99.85 20 | 94.07 74 | 100.00 1 | 98.67 56 | 100.00 1 | 99.98 43 |
|
#test# | | | 98.59 27 | 98.41 26 | 99.14 50 | 99.96 8 | 97.43 82 | 99.95 31 | 98.61 75 | 95.00 68 | 99.31 45 | 99.85 20 | 94.22 68 | 100.00 1 | 98.78 51 | 99.98 25 | 99.98 43 |
|
ACMMPR | | | 98.50 34 | 98.32 35 | 99.05 64 | 99.96 8 | 97.18 96 | 99.95 31 | 98.60 77 | 94.77 73 | 99.31 45 | 99.84 34 | 93.73 84 | 100.00 1 | 98.70 54 | 99.98 25 | 99.98 43 |
|
NCCC | | | 99.37 2 | 99.25 2 | 99.71 5 | 99.96 8 | 99.15 9 | 99.97 12 | 98.62 73 | 98.02 6 | 99.90 2 | 99.95 3 | 97.33 9 | 100.00 1 | 99.54 20 | 100.00 1 | 100.00 1 |
|
CP-MVS | | | 98.45 37 | 98.32 35 | 98.87 77 | 99.96 8 | 96.62 111 | 99.97 12 | 98.39 125 | 94.43 83 | 98.90 63 | 99.87 14 | 94.30 66 | 100.00 1 | 99.04 39 | 99.99 13 | 99.99 11 |
|
XVS | | | 98.70 22 | 98.55 22 | 99.15 48 | 99.94 14 | 97.50 78 | 99.94 45 | 98.42 119 | 96.22 39 | 99.41 39 | 99.78 49 | 94.34 63 | 99.96 42 | 98.92 44 | 99.95 39 | 99.99 11 |
|
test_prior3 | | | 98.99 11 | 98.84 12 | 99.43 26 | 99.94 14 | 98.49 48 | 99.95 31 | 98.65 66 | 95.78 50 | 99.73 13 | 99.76 55 | 96.00 25 | 99.80 87 | 99.78 9 | 100.00 1 | 99.99 11 |
|
X-MVStestdata | | | 93.83 172 | 92.06 194 | 99.15 48 | 99.94 14 | 97.50 78 | 99.94 45 | 98.42 119 | 96.22 39 | 99.41 39 | 41.37 354 | 94.34 63 | 99.96 42 | 98.92 44 | 99.95 39 | 99.99 11 |
|
test_prior | | | | | 99.43 26 | 99.94 14 | 98.49 48 | | 98.65 66 | | | | | 99.80 87 | | | 99.99 11 |
|
MSLP-MVS++ | | | 99.13 5 | 99.01 6 | 99.49 22 | 99.94 14 | 98.46 50 | 99.98 6 | 98.86 52 | 97.10 15 | 99.80 8 | 99.94 4 | 95.92 29 | 100.00 1 | 99.51 21 | 100.00 1 | 100.00 1 |
|
APDe-MVS | | | 99.06 8 | 98.91 10 | 99.51 20 | 99.94 14 | 98.76 30 | 99.91 56 | 98.39 125 | 97.20 14 | 99.46 34 | 99.85 20 | 95.53 36 | 99.79 89 | 99.86 5 | 100.00 1 | 99.99 11 |
|
MP-MVS | | | 98.23 49 | 97.97 49 | 99.03 66 | 99.94 14 | 97.17 99 | 99.95 31 | 98.39 125 | 94.70 76 | 98.26 91 | 99.81 42 | 91.84 118 | 100.00 1 | 98.85 48 | 99.97 34 | 99.93 65 |
|
CDPH-MVS | | | 98.65 23 | 98.36 33 | 99.49 22 | 99.94 14 | 98.73 31 | 99.87 71 | 98.33 134 | 93.97 101 | 99.76 11 | 99.87 14 | 94.99 49 | 99.75 96 | 98.55 63 | 100.00 1 | 99.98 43 |
|
PAPM_NR | | | 98.12 52 | 97.93 52 | 98.70 84 | 99.94 14 | 96.13 129 | 99.82 95 | 98.43 111 | 94.56 79 | 97.52 105 | 99.70 68 | 94.40 59 | 99.98 31 | 97.00 104 | 99.98 25 | 99.99 11 |
|
MG-MVS | | | 98.91 14 | 98.65 16 | 99.68 7 | 99.94 14 | 99.07 11 | 99.64 149 | 99.44 22 | 97.33 12 | 99.00 61 | 99.72 64 | 94.03 75 | 99.98 31 | 98.73 53 | 100.00 1 | 100.00 1 |
|
HSP-MVS | | | 99.07 6 | 99.11 4 | 98.95 73 | 99.93 24 | 97.24 93 | 99.95 31 | 98.32 135 | 97.50 10 | 99.52 31 | 99.88 11 | 97.43 6 | 99.71 104 | 99.50 22 | 99.98 25 | 99.89 71 |
|
agg_prior1 | | | 98.88 15 | 98.66 15 | 99.54 17 | 99.93 24 | 98.77 25 | 99.96 19 | 98.43 111 | 94.63 78 | 99.63 20 | 99.85 20 | 95.79 31 | 99.85 78 | 99.72 16 | 99.99 13 | 99.99 11 |
|
agg_prior | | | | | | 99.93 24 | 98.77 25 | | 98.43 111 | | 99.63 20 | | | 99.85 78 | | | |
|
TEST9 | | | | | | 99.92 27 | 98.92 15 | 99.96 19 | 98.43 111 | 93.90 105 | 99.71 15 | 99.86 16 | 95.88 30 | 99.85 78 | | | |
|
train_agg | | | 98.88 15 | 98.65 16 | 99.59 13 | 99.92 27 | 98.92 15 | 99.96 19 | 98.43 111 | 94.35 85 | 99.71 15 | 99.86 16 | 95.94 27 | 99.85 78 | 99.69 18 | 99.98 25 | 99.99 11 |
|
test_8 | | | | | | 99.92 27 | 98.88 18 | 99.96 19 | 98.43 111 | 94.35 85 | 99.69 17 | 99.85 20 | 95.94 27 | 99.85 78 | | | |
|
agg_prior3 | | | 98.84 17 | 98.62 18 | 99.47 25 | 99.92 27 | 98.56 44 | 99.96 19 | 98.43 111 | 94.07 95 | 99.67 18 | 99.85 20 | 96.05 23 | 99.85 78 | 99.69 18 | 99.98 25 | 99.99 11 |
|
PGM-MVS | | | 98.34 43 | 98.13 43 | 98.99 70 | 99.92 27 | 97.00 101 | 99.75 116 | 99.50 20 | 93.90 105 | 99.37 43 | 99.76 55 | 93.24 94 | 100.00 1 | 97.75 90 | 99.96 36 | 99.98 43 |
|
ACMMP | | | 97.74 65 | 97.44 63 | 98.66 87 | 99.92 27 | 96.13 129 | 99.18 197 | 99.45 21 | 94.84 72 | 96.41 129 | 99.71 66 | 91.40 121 | 99.99 27 | 97.99 80 | 98.03 120 | 99.87 74 |
Qingshan Xu, Weihang Kong, Wenbing Tao, Marc Pollefeys: Multi-Scale Geometric Consistency Guided and Planar Prior Assisted Multi-View Stereo. IEEE Transactions on Pattern Analysis and Machine Intelligence |
HPM-MVS++ | | | 99.07 6 | 98.88 11 | 99.63 8 | 99.90 33 | 99.02 12 | 99.95 31 | 98.56 83 | 97.56 9 | 99.44 36 | 99.85 20 | 95.38 38 | 100.00 1 | 99.31 29 | 99.99 13 | 99.87 74 |
|
APD-MVS | | | 98.62 24 | 98.35 34 | 99.41 30 | 99.90 33 | 98.51 47 | 99.87 71 | 98.36 131 | 94.08 94 | 99.74 12 | 99.73 63 | 94.08 73 | 99.74 100 | 99.42 26 | 99.99 13 | 99.99 11 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
DeepC-MVS_fast | | 96.59 1 | 98.81 18 | 98.54 23 | 99.62 11 | 99.90 33 | 98.85 20 | 99.24 193 | 98.47 102 | 98.14 4 | 99.08 55 | 99.91 6 | 93.09 97 | 100.00 1 | 99.04 39 | 99.99 13 | 100.00 1 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
test_part2 | | | | | | 99.89 36 | 99.25 6 | | | | 99.49 32 | | | | | | |
|
ESAPD | | | 99.18 4 | 98.99 7 | 99.75 3 | 99.89 36 | 99.25 6 | 99.88 66 | 98.41 121 | 96.14 43 | 99.49 32 | 99.91 6 | 97.20 11 | 100.00 1 | 99.99 1 | 99.99 13 | 99.99 11 |
|
CSCG | | | 97.10 84 | 97.04 75 | 97.27 152 | 99.89 36 | 91.92 233 | 99.90 59 | 99.07 32 | 88.67 232 | 95.26 150 | 99.82 39 | 93.17 96 | 99.98 31 | 98.15 72 | 99.47 88 | 99.90 70 |
|
PHI-MVS | | | 98.41 40 | 98.21 38 | 99.03 66 | 99.86 39 | 97.10 100 | 99.98 6 | 98.80 57 | 90.78 202 | 99.62 22 | 99.78 49 | 95.30 39 | 100.00 1 | 99.80 7 | 99.93 48 | 99.99 11 |
|
MPTG | | | 98.33 44 | 98.00 47 | 99.30 37 | 99.85 40 | 97.93 65 | 99.80 100 | 98.28 139 | 95.76 52 | 97.18 112 | 99.88 11 | 92.74 102 | 100.00 1 | 98.67 56 | 99.88 56 | 99.99 11 |
|
MTAPA | | | 98.29 45 | 97.96 51 | 99.30 37 | 99.85 40 | 97.93 65 | 99.39 178 | 98.28 139 | 95.76 52 | 97.18 112 | 99.88 11 | 92.74 102 | 100.00 1 | 98.67 56 | 99.88 56 | 99.99 11 |
|
Regformer-1 | | | 98.79 19 | 98.60 20 | 99.36 35 | 99.85 40 | 98.34 52 | 99.87 71 | 98.52 90 | 96.05 45 | 99.41 39 | 99.79 44 | 94.93 51 | 99.76 93 | 99.07 34 | 99.90 52 | 99.99 11 |
|
Regformer-2 | | | 98.78 20 | 98.59 21 | 99.36 35 | 99.85 40 | 98.32 53 | 99.87 71 | 98.52 90 | 96.04 46 | 99.41 39 | 99.79 44 | 94.92 52 | 99.76 93 | 99.05 35 | 99.90 52 | 99.98 43 |
|
LS3D | | | 95.84 133 | 95.11 141 | 98.02 129 | 99.85 40 | 95.10 158 | 98.74 238 | 98.50 100 | 87.22 256 | 93.66 174 | 99.86 16 | 87.45 164 | 99.95 50 | 90.94 195 | 99.81 67 | 99.02 177 |
|
Regformer-3 | | | 98.58 28 | 98.41 26 | 99.10 56 | 99.84 45 | 97.57 74 | 99.66 142 | 98.52 90 | 95.79 49 | 99.01 59 | 99.77 51 | 94.40 59 | 99.75 96 | 98.82 49 | 99.83 61 | 99.98 43 |
|
Regformer-4 | | | 98.56 29 | 98.39 29 | 99.08 58 | 99.84 45 | 97.52 76 | 99.66 142 | 98.52 90 | 95.76 52 | 99.01 59 | 99.77 51 | 94.33 65 | 99.75 96 | 98.80 50 | 99.83 61 | 99.98 43 |
|
HPM-MVS | | | 97.96 56 | 97.72 55 | 98.68 85 | 99.84 45 | 96.39 119 | 99.90 59 | 98.17 151 | 92.61 145 | 98.62 75 | 99.57 83 | 91.87 117 | 99.67 111 | 98.87 47 | 99.99 13 | 99.99 11 |
|
EI-MVSNet-Vis-set | | | 98.27 46 | 98.11 44 | 98.75 82 | 99.83 48 | 96.59 113 | 99.40 175 | 98.51 96 | 95.29 64 | 98.51 79 | 99.76 55 | 93.60 88 | 99.71 104 | 98.53 64 | 99.52 85 | 99.95 62 |
|
PLC | | 95.54 3 | 97.93 58 | 97.89 53 | 98.05 128 | 99.82 49 | 94.77 166 | 99.92 52 | 98.46 104 | 93.93 104 | 97.20 110 | 99.27 101 | 95.44 37 | 99.97 40 | 97.41 94 | 99.51 87 | 99.41 133 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
APD-MVS_3200maxsize | | | 98.25 48 | 98.08 45 | 98.78 80 | 99.81 50 | 96.60 112 | 99.82 95 | 98.30 137 | 93.95 103 | 99.37 43 | 99.77 51 | 92.84 99 | 99.76 93 | 98.95 41 | 99.92 50 | 99.97 53 |
|
EI-MVSNet-UG-set | | | 98.14 51 | 97.99 48 | 98.60 92 | 99.80 51 | 96.27 120 | 99.36 182 | 98.50 100 | 95.21 66 | 98.30 88 | 99.75 60 | 93.29 93 | 99.73 103 | 98.37 68 | 99.30 95 | 99.81 79 |
|
HPM-MVS_fast | | | 97.80 62 | 97.50 62 | 98.68 85 | 99.79 52 | 96.42 116 | 99.88 66 | 98.16 154 | 91.75 175 | 98.94 62 | 99.54 86 | 91.82 119 | 99.65 113 | 97.62 92 | 99.99 13 | 99.99 11 |
|
旧先验1 | | | | | | 99.76 53 | 97.52 76 | | 98.64 69 | | | 99.85 20 | 95.63 33 | | | 99.94 43 | 99.99 11 |
|
OMC-MVS | | | 97.28 77 | 97.23 68 | 97.41 147 | 99.76 53 | 93.36 199 | 99.65 145 | 97.95 172 | 96.03 47 | 97.41 107 | 99.70 68 | 89.61 140 | 99.51 118 | 96.73 110 | 98.25 115 | 99.38 140 |
|
新几何1 | | | | | 99.42 29 | 99.75 55 | 98.27 55 | | 98.63 72 | 92.69 139 | 99.55 27 | 99.82 39 | 94.40 59 | 100.00 1 | 91.21 188 | 99.94 43 | 99.99 11 |
|
MP-MVS-pluss | | | 98.07 54 | 97.64 57 | 99.38 34 | 99.74 56 | 98.41 51 | 99.74 119 | 98.18 150 | 93.35 119 | 96.45 126 | 99.85 20 | 92.64 105 | 99.97 40 | 98.91 46 | 99.89 54 | 99.77 84 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
TSAR-MVS + MP. | | | 98.93 12 | 98.77 13 | 99.41 30 | 99.74 56 | 98.67 34 | 99.77 109 | 98.38 128 | 96.73 26 | 99.88 3 | 99.74 62 | 94.89 53 | 99.59 115 | 99.80 7 | 99.98 25 | 99.97 53 |
|
1121 | | | 98.03 55 | 97.57 61 | 99.40 32 | 99.74 56 | 98.21 56 | 98.31 269 | 98.62 73 | 92.78 134 | 99.53 28 | 99.83 36 | 95.08 43 | 100.00 1 | 94.36 142 | 99.92 50 | 99.99 11 |
|
test12 | | | | | 99.43 26 | 99.74 56 | 98.56 44 | | 98.40 123 | | 99.65 19 | | 94.76 54 | 99.75 96 | | 99.98 25 | 99.99 11 |
|
原ACMM1 | | | | | 98.96 72 | 99.73 60 | 96.99 102 | | 98.51 96 | 94.06 98 | 99.62 22 | 99.85 20 | 94.97 50 | 99.96 42 | 95.11 127 | 99.95 39 | 99.92 68 |
|
TSAR-MVS + GP. | | | 98.60 25 | 98.51 24 | 98.86 78 | 99.73 60 | 96.63 110 | 99.97 12 | 97.92 175 | 98.07 5 | 98.76 68 | 99.55 84 | 95.00 48 | 99.94 58 | 99.91 4 | 97.68 124 | 99.99 11 |
|
CANet | | | 98.27 46 | 97.82 54 | 99.63 8 | 99.72 62 | 99.10 10 | 99.98 6 | 98.51 96 | 97.00 18 | 98.52 78 | 99.71 66 | 87.80 160 | 99.95 50 | 99.75 11 | 99.38 92 | 99.83 77 |
|
F-COLMAP | | | 96.93 89 | 96.95 77 | 96.87 160 | 99.71 63 | 91.74 239 | 99.85 87 | 97.95 172 | 93.11 124 | 95.72 143 | 99.16 109 | 92.35 107 | 99.94 58 | 95.32 125 | 99.35 93 | 98.92 179 |
|
SD-MVS | | | 98.92 13 | 98.70 14 | 99.56 15 | 99.70 64 | 98.73 31 | 99.94 45 | 98.34 133 | 96.38 34 | 99.81 7 | 99.76 55 | 94.59 56 | 99.98 31 | 99.84 6 | 99.96 36 | 99.97 53 |
|
abl_6 | | | 97.67 67 | 97.34 65 | 98.66 87 | 99.68 65 | 96.11 133 | 99.68 137 | 98.14 157 | 93.80 108 | 99.27 48 | 99.70 68 | 88.65 156 | 99.98 31 | 97.46 93 | 99.72 71 | 99.89 71 |
|
ACMMP_Plus | | | 98.49 35 | 98.14 42 | 99.54 17 | 99.66 66 | 98.62 39 | 99.85 87 | 98.37 130 | 94.68 77 | 99.53 28 | 99.83 36 | 92.87 98 | 100.00 1 | 98.66 59 | 99.84 60 | 99.99 11 |
|
DeepPCF-MVS | | 95.94 2 | 97.71 66 | 98.98 8 | 93.92 245 | 99.63 67 | 81.76 318 | 99.96 19 | 98.56 83 | 99.47 1 | 99.19 52 | 99.99 1 | 94.16 72 | 100.00 1 | 99.92 3 | 99.93 48 | 100.00 1 |
|
EPNet | | | 98.49 35 | 98.40 28 | 98.77 81 | 99.62 68 | 96.80 108 | 99.90 59 | 99.51 19 | 97.60 8 | 99.20 50 | 99.36 99 | 93.71 85 | 99.91 64 | 97.99 80 | 98.71 105 | 99.61 106 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
MVS_0304 | | | 97.52 70 | 96.79 82 | 99.69 6 | 99.59 69 | 99.30 4 | 99.97 12 | 98.01 166 | 96.99 19 | 98.84 64 | 99.79 44 | 78.90 254 | 99.96 42 | 99.74 13 | 99.32 94 | 99.81 79 |
|
PVSNet_BlendedMVS | | | 96.05 128 | 95.82 120 | 96.72 165 | 99.59 69 | 96.99 102 | 99.95 31 | 99.10 29 | 94.06 98 | 98.27 89 | 95.80 228 | 89.00 151 | 99.95 50 | 99.12 32 | 87.53 236 | 93.24 288 |
|
PVSNet_Blended | | | 97.94 57 | 97.64 57 | 98.83 79 | 99.59 69 | 96.99 102 | 100.00 1 | 99.10 29 | 95.38 61 | 98.27 89 | 99.08 112 | 89.00 151 | 99.95 50 | 99.12 32 | 99.25 96 | 99.57 114 |
|
PatchMatch-RL | | | 96.04 129 | 95.40 131 | 97.95 130 | 99.59 69 | 95.22 157 | 99.52 163 | 99.07 32 | 93.96 102 | 96.49 124 | 98.35 167 | 82.28 202 | 99.82 86 | 90.15 208 | 99.22 97 | 98.81 182 |
|
test222 | | | | | | 99.55 73 | 97.41 85 | 99.34 183 | 98.55 87 | 91.86 172 | 99.27 48 | 99.83 36 | 93.84 82 | | | 99.95 39 | 99.99 11 |
|
CNLPA | | | 97.76 64 | 97.38 64 | 98.92 75 | 99.53 74 | 96.84 106 | 99.87 71 | 98.14 157 | 93.78 109 | 96.55 123 | 99.69 71 | 92.28 109 | 99.98 31 | 97.13 100 | 99.44 90 | 99.93 65 |
|
API-MVS | | | 97.86 59 | 97.66 56 | 98.47 106 | 99.52 75 | 95.41 150 | 99.47 169 | 98.87 51 | 91.68 176 | 98.84 64 | 99.85 20 | 92.34 108 | 99.99 27 | 98.44 66 | 99.96 36 | 100.00 1 |
|
PVSNet | | 91.05 13 | 97.13 83 | 96.69 85 | 98.45 108 | 99.52 75 | 95.81 136 | 99.95 31 | 99.65 15 | 94.73 75 | 99.04 57 | 99.21 107 | 84.48 190 | 99.95 50 | 94.92 129 | 98.74 104 | 99.58 113 |
|
114514_t | | | 97.41 75 | 96.83 79 | 99.14 50 | 99.51 77 | 97.83 67 | 99.89 64 | 98.27 142 | 88.48 235 | 99.06 56 | 99.66 77 | 90.30 135 | 99.64 114 | 96.32 113 | 99.97 34 | 99.96 57 |
|
testdata | | | | | 98.42 111 | 99.47 78 | 95.33 152 | | 98.56 83 | 93.78 109 | 99.79 10 | 99.85 20 | 93.64 87 | 99.94 58 | 94.97 128 | 99.94 43 | 100.00 1 |
|
MAR-MVS | | | 97.43 71 | 97.19 69 | 98.15 124 | 99.47 78 | 94.79 165 | 99.05 214 | 98.76 58 | 92.65 143 | 98.66 73 | 99.82 39 | 88.52 157 | 99.98 31 | 98.12 73 | 99.63 76 | 99.67 96 |
Zhenyu Xu, Yiguang Liu, Xuelei Shi, Ying Wang, Yunan Zheng: MARMVS: Matching Ambiguity Reduced Multiple View Stereo for Efficient Large Scale Scene Reconstruction. CVPR 2020 |
DP-MVS | | | 94.54 161 | 93.42 172 | 97.91 132 | 99.46 80 | 94.04 176 | 98.93 225 | 97.48 215 | 81.15 310 | 90.04 206 | 99.55 84 | 87.02 169 | 99.95 50 | 88.97 223 | 98.11 116 | 99.73 89 |
|
MVS_111021_LR | | | 98.42 39 | 98.38 30 | 98.53 99 | 99.39 81 | 95.79 137 | 99.87 71 | 99.86 2 | 96.70 27 | 98.78 67 | 99.79 44 | 92.03 114 | 99.90 65 | 99.17 31 | 99.86 59 | 99.88 73 |
|
CHOSEN 280x420 | | | 99.01 10 | 99.03 5 | 98.95 73 | 99.38 82 | 98.87 19 | 98.46 259 | 99.42 24 | 97.03 17 | 99.02 58 | 99.09 111 | 99.35 1 | 98.21 196 | 99.73 15 | 99.78 68 | 99.77 84 |
|
MVS_111021_HR | | | 98.72 21 | 98.62 18 | 99.01 69 | 99.36 83 | 97.18 96 | 99.93 50 | 99.90 1 | 96.81 24 | 98.67 72 | 99.77 51 | 93.92 77 | 99.89 68 | 99.27 30 | 99.94 43 | 99.96 57 |
|
TAPA-MVS | | 92.12 8 | 94.42 165 | 93.60 165 | 96.90 159 | 99.33 84 | 91.78 237 | 99.78 104 | 98.00 167 | 89.89 214 | 94.52 166 | 99.47 90 | 91.97 115 | 99.18 135 | 69.90 321 | 99.52 85 | 99.73 89 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
DeepC-MVS | | 94.51 4 | 96.92 90 | 96.40 92 | 98.45 108 | 99.16 85 | 95.90 135 | 99.66 142 | 98.06 163 | 96.37 37 | 94.37 169 | 99.49 89 | 83.29 198 | 99.90 65 | 97.63 91 | 99.61 80 | 99.55 116 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
DELS-MVS | | | 98.54 31 | 98.22 37 | 99.50 21 | 99.15 86 | 98.65 37 | 100.00 1 | 98.58 79 | 97.70 7 | 98.21 93 | 99.24 105 | 92.58 106 | 99.94 58 | 98.63 61 | 99.94 43 | 99.92 68 |
Christian Sormann, Emanuele Santellani, Mattia Rossi, Andreas Kuhn, Friedrich Fraundorfer: DELS-MVS: Deep Epipolar Line Search for Multi-View Stereo. Winter Conference on Applications of Computer Vision (WACV), 2023 |
tfpn_ndepth | | | 97.21 81 | 96.63 86 | 98.92 75 | 99.06 87 | 98.28 54 | 99.95 31 | 98.91 41 | 92.96 126 | 96.49 124 | 98.67 150 | 97.40 7 | 99.07 137 | 91.87 184 | 94.38 177 | 99.41 133 |
|
HyFIR lowres test | | | 96.66 103 | 96.43 91 | 97.36 150 | 99.05 88 | 93.91 179 | 99.70 131 | 99.80 3 | 90.54 203 | 96.26 131 | 98.08 172 | 92.15 112 | 98.23 195 | 96.84 109 | 95.46 166 | 99.93 65 |
|
LFMVS | | | 94.75 156 | 93.56 168 | 98.30 118 | 99.03 89 | 95.70 144 | 98.74 238 | 97.98 169 | 87.81 243 | 98.47 80 | 99.39 96 | 67.43 312 | 99.53 116 | 98.01 78 | 95.20 169 | 99.67 96 |
|
AllTest | | | 92.48 197 | 91.64 197 | 95.00 202 | 99.01 90 | 88.43 282 | 98.94 224 | 96.82 280 | 86.50 264 | 88.71 238 | 98.47 165 | 74.73 284 | 99.88 74 | 85.39 263 | 96.18 151 | 96.71 201 |
|
TestCases | | | | | 95.00 202 | 99.01 90 | 88.43 282 | | 96.82 280 | 86.50 264 | 88.71 238 | 98.47 165 | 74.73 284 | 99.88 74 | 85.39 263 | 96.18 151 | 96.71 201 |
|
tfpn1000 | | | 96.90 91 | 96.29 94 | 98.74 83 | 99.00 92 | 98.09 60 | 99.92 52 | 98.91 41 | 92.08 165 | 95.85 137 | 98.65 152 | 97.39 8 | 98.83 145 | 90.56 199 | 94.23 185 | 99.31 148 |
|
COLMAP_ROB | | 90.47 14 | 92.18 203 | 91.49 201 | 94.25 233 | 99.00 92 | 88.04 287 | 98.42 264 | 96.70 282 | 82.30 300 | 88.43 243 | 99.01 116 | 76.97 265 | 99.85 78 | 86.11 258 | 96.50 149 | 94.86 209 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
HY-MVS | | 92.50 7 | 97.79 63 | 97.17 71 | 99.63 8 | 98.98 94 | 99.32 3 | 97.49 290 | 99.52 17 | 95.69 56 | 98.32 87 | 97.41 184 | 93.32 91 | 99.77 91 | 98.08 77 | 95.75 162 | 99.81 79 |
|
VNet | | | 97.21 81 | 96.57 89 | 99.13 55 | 98.97 95 | 97.82 68 | 99.03 216 | 99.21 28 | 94.31 87 | 99.18 53 | 98.88 127 | 86.26 176 | 99.89 68 | 98.93 43 | 94.32 182 | 99.69 94 |
|
thres200 | | | 96.96 87 | 96.21 96 | 99.22 40 | 98.97 95 | 98.84 21 | 99.85 87 | 99.71 5 | 93.17 122 | 96.26 131 | 98.88 127 | 89.87 138 | 99.51 118 | 94.26 146 | 94.91 171 | 99.31 148 |
|
tfpn200view9 | | | 96.79 94 | 95.99 101 | 99.19 41 | 98.94 97 | 98.82 22 | 99.78 104 | 99.71 5 | 92.86 127 | 96.02 134 | 98.87 129 | 89.33 141 | 99.50 120 | 93.84 153 | 94.57 172 | 99.27 153 |
|
thres400 | | | 96.78 95 | 95.99 101 | 99.16 45 | 98.94 97 | 98.82 22 | 99.78 104 | 99.71 5 | 92.86 127 | 96.02 134 | 98.87 129 | 89.33 141 | 99.50 120 | 93.84 153 | 94.57 172 | 99.16 164 |
|
canonicalmvs | | | 97.09 85 | 96.32 93 | 99.39 33 | 98.93 99 | 98.95 14 | 99.72 129 | 97.35 227 | 94.45 81 | 97.88 99 | 99.42 92 | 86.71 171 | 99.52 117 | 98.48 65 | 93.97 195 | 99.72 91 |
|
EPNet_dtu | | | 95.71 136 | 95.39 132 | 96.66 167 | 98.92 100 | 93.41 195 | 99.57 155 | 98.90 49 | 96.19 41 | 97.52 105 | 98.56 159 | 92.65 104 | 97.36 223 | 77.89 307 | 98.33 111 | 99.20 159 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
WTY-MVS | | | 98.10 53 | 97.60 59 | 99.60 12 | 98.92 100 | 99.28 5 | 99.89 64 | 99.52 17 | 95.58 58 | 98.24 92 | 99.39 96 | 93.33 90 | 99.74 100 | 97.98 82 | 95.58 165 | 99.78 83 |
|
CHOSEN 1792x2688 | | | 96.81 93 | 96.53 90 | 97.64 139 | 98.91 102 | 93.07 205 | 99.65 145 | 99.80 3 | 95.64 57 | 95.39 147 | 98.86 131 | 84.35 192 | 99.90 65 | 96.98 105 | 99.16 98 | 99.95 62 |
|
conf200view11 | | | 96.73 100 | 95.92 109 | 99.16 45 | 98.90 103 | 98.77 25 | 99.74 119 | 99.71 5 | 92.59 147 | 95.84 138 | 98.86 131 | 89.25 143 | 99.50 120 | 93.84 153 | 94.57 172 | 99.20 159 |
|
thres100view900 | | | 96.74 98 | 95.92 109 | 99.18 42 | 98.90 103 | 98.77 25 | 99.74 119 | 99.71 5 | 92.59 147 | 95.84 138 | 98.86 131 | 89.25 143 | 99.50 120 | 93.84 153 | 94.57 172 | 99.27 153 |
|
thres600view7 | | | 96.69 101 | 95.87 119 | 99.14 50 | 98.90 103 | 98.78 24 | 99.74 119 | 99.71 5 | 92.59 147 | 95.84 138 | 98.86 131 | 89.25 143 | 99.50 120 | 93.44 163 | 94.50 176 | 99.16 164 |
|
MSDG | | | 94.37 167 | 93.36 176 | 97.40 148 | 98.88 106 | 93.95 178 | 99.37 180 | 97.38 225 | 85.75 277 | 90.80 196 | 99.17 108 | 84.11 193 | 99.88 74 | 86.35 255 | 98.43 109 | 98.36 187 |
|
view600 | | | 96.46 114 | 95.59 124 | 99.06 60 | 98.87 107 | 98.60 40 | 99.69 132 | 99.71 5 | 92.20 159 | 95.23 151 | 98.80 142 | 89.17 146 | 99.43 127 | 92.29 175 | 94.37 178 | 99.16 164 |
|
view800 | | | 96.46 114 | 95.59 124 | 99.06 60 | 98.87 107 | 98.60 40 | 99.69 132 | 99.71 5 | 92.20 159 | 95.23 151 | 98.80 142 | 89.17 146 | 99.43 127 | 92.29 175 | 94.37 178 | 99.16 164 |
|
conf0.05thres1000 | | | 96.46 114 | 95.59 124 | 99.06 60 | 98.87 107 | 98.60 40 | 99.69 132 | 99.71 5 | 92.20 159 | 95.23 151 | 98.80 142 | 89.17 146 | 99.43 127 | 92.29 175 | 94.37 178 | 99.16 164 |
|
tfpn | | | 96.46 114 | 95.59 124 | 99.06 60 | 98.87 107 | 98.60 40 | 99.69 132 | 99.71 5 | 92.20 159 | 95.23 151 | 98.80 142 | 89.17 146 | 99.43 127 | 92.29 175 | 94.37 178 | 99.16 164 |
|
PVSNet_Blended_VisFu | | | 97.27 78 | 96.81 80 | 98.66 87 | 98.81 111 | 96.67 109 | 99.92 52 | 98.64 69 | 94.51 80 | 96.38 130 | 98.49 161 | 89.05 150 | 99.88 74 | 97.10 102 | 98.34 110 | 99.43 131 |
|
PS-MVSNAJ | | | 98.44 38 | 98.20 39 | 99.16 45 | 98.80 112 | 98.92 15 | 99.54 161 | 98.17 151 | 97.34 11 | 99.85 5 | 99.85 20 | 91.20 124 | 99.89 68 | 99.41 27 | 99.67 74 | 98.69 185 |
|
CANet_DTU | | | 96.76 96 | 96.15 97 | 98.60 92 | 98.78 113 | 97.53 75 | 99.84 90 | 97.63 196 | 97.25 13 | 99.20 50 | 99.64 79 | 81.36 224 | 99.98 31 | 92.77 173 | 98.89 100 | 98.28 188 |
|
alignmvs | | | 97.81 61 | 97.33 66 | 99.25 39 | 98.77 114 | 98.66 35 | 99.99 3 | 98.44 106 | 94.40 84 | 98.41 82 | 99.47 90 | 93.65 86 | 99.42 131 | 98.57 62 | 94.26 184 | 99.67 96 |
|
SteuartSystems-ACMMP | | | 99.02 9 | 98.97 9 | 99.18 42 | 98.72 115 | 97.71 70 | 99.98 6 | 98.44 106 | 96.85 20 | 99.80 8 | 99.91 6 | 97.57 4 | 99.85 78 | 99.44 25 | 99.99 13 | 99.99 11 |
Skip Steuart: Steuart Systems R&D Blog. |
xiu_mvs_v2_base | | | 98.23 49 | 97.97 49 | 99.02 68 | 98.69 116 | 98.66 35 | 99.52 163 | 98.08 162 | 97.05 16 | 99.86 4 | 99.86 16 | 90.65 132 | 99.71 104 | 99.39 28 | 98.63 106 | 98.69 185 |
|
conf0.01 | | | 96.52 111 | 95.88 112 | 98.41 114 | 98.59 117 | 97.38 86 | 99.87 71 | 98.91 41 | 91.32 186 | 95.22 155 | 98.83 136 | 96.57 15 | 98.66 157 | 89.55 213 | 94.09 187 | 99.20 159 |
|
conf0.002 | | | 96.52 111 | 95.88 112 | 98.41 114 | 98.59 117 | 97.38 86 | 99.87 71 | 98.91 41 | 91.32 186 | 95.22 155 | 98.83 136 | 96.57 15 | 98.66 157 | 89.55 213 | 94.09 187 | 99.20 159 |
|
thresconf0.02 | | | 96.53 106 | 95.88 112 | 98.48 102 | 98.59 117 | 97.38 86 | 99.87 71 | 98.91 41 | 91.32 186 | 95.22 155 | 98.83 136 | 96.57 15 | 98.66 157 | 89.55 213 | 94.09 187 | 99.40 136 |
|
tfpn_n400 | | | 96.53 106 | 95.88 112 | 98.48 102 | 98.59 117 | 97.38 86 | 99.87 71 | 98.91 41 | 91.32 186 | 95.22 155 | 98.83 136 | 96.57 15 | 98.66 157 | 89.55 213 | 94.09 187 | 99.40 136 |
|
tfpnconf | | | 96.53 106 | 95.88 112 | 98.48 102 | 98.59 117 | 97.38 86 | 99.87 71 | 98.91 41 | 91.32 186 | 95.22 155 | 98.83 136 | 96.57 15 | 98.66 157 | 89.55 213 | 94.09 187 | 99.40 136 |
|
tfpnview11 | | | 96.53 106 | 95.88 112 | 98.48 102 | 98.59 117 | 97.38 86 | 99.87 71 | 98.91 41 | 91.32 186 | 95.22 155 | 98.83 136 | 96.57 15 | 98.66 157 | 89.55 213 | 94.09 187 | 99.40 136 |
|
MVSTER | | | 95.53 139 | 95.22 137 | 96.45 171 | 98.56 123 | 97.72 69 | 99.91 56 | 97.67 194 | 92.38 156 | 91.39 191 | 97.14 190 | 97.24 10 | 97.30 231 | 94.80 133 | 87.85 231 | 94.34 228 |
|
VDD-MVS | | | 93.77 176 | 92.94 179 | 96.27 176 | 98.55 124 | 90.22 263 | 98.77 237 | 97.79 187 | 90.85 200 | 96.82 118 | 99.42 92 | 61.18 328 | 99.77 91 | 98.95 41 | 94.13 186 | 98.82 181 |
|
tpmvs | | | 94.28 168 | 93.57 167 | 96.40 173 | 98.55 124 | 91.50 248 | 95.70 318 | 98.55 87 | 87.47 251 | 92.15 187 | 94.26 284 | 91.42 120 | 98.95 142 | 88.15 229 | 95.85 159 | 98.76 184 |
|
UGNet | | | 95.33 143 | 94.57 149 | 97.62 140 | 98.55 124 | 94.85 161 | 98.67 245 | 99.32 27 | 95.75 55 | 96.80 119 | 96.27 220 | 72.18 294 | 99.96 42 | 94.58 139 | 99.05 99 | 98.04 192 |
Wanjuan Su, Qingshan Xu, Wenbing Tao: Uncertainty-guided Multi-view Stereo Network for Depth Estimation. IEEE Transactions on Circuits and Systems for Video Technology, 2022 |
PCF-MVS | | 94.20 5 | 95.18 145 | 94.10 157 | 98.43 110 | 98.55 124 | 95.99 134 | 97.91 286 | 97.31 231 | 90.35 206 | 89.48 226 | 99.22 106 | 85.19 187 | 99.89 68 | 90.40 204 | 98.47 108 | 99.41 133 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
BH-w/o | | | 95.71 136 | 95.38 133 | 96.68 166 | 98.49 128 | 92.28 224 | 99.84 90 | 97.50 213 | 92.12 164 | 92.06 188 | 98.79 147 | 84.69 188 | 98.67 155 | 95.29 126 | 99.66 75 | 99.09 175 |
|
EPMVS | | | 96.53 106 | 96.01 100 | 98.09 127 | 98.43 129 | 96.12 132 | 96.36 307 | 99.43 23 | 93.53 116 | 97.64 102 | 95.04 259 | 94.41 58 | 98.38 184 | 91.13 190 | 98.11 116 | 99.75 86 |
|
sss | | | 97.57 69 | 97.03 76 | 99.18 42 | 98.37 130 | 98.04 62 | 99.73 124 | 99.38 25 | 93.46 117 | 98.76 68 | 99.06 113 | 91.21 123 | 99.89 68 | 96.33 112 | 97.01 142 | 99.62 104 |
|
BH-untuned | | | 95.18 145 | 94.83 144 | 96.22 177 | 98.36 131 | 91.22 250 | 99.80 100 | 97.32 230 | 90.91 198 | 91.08 193 | 98.67 150 | 83.51 195 | 98.54 166 | 94.23 147 | 99.61 80 | 98.92 179 |
|
FMVSNet3 | | | 92.69 194 | 91.58 198 | 95.99 181 | 98.29 132 | 97.42 84 | 99.26 192 | 97.62 198 | 89.80 215 | 89.68 218 | 95.32 245 | 81.62 219 | 96.27 282 | 87.01 248 | 85.65 244 | 94.29 231 |
|
PMMVS | | | 96.76 96 | 96.76 84 | 96.76 163 | 98.28 133 | 92.10 228 | 99.91 56 | 97.98 169 | 94.12 92 | 99.53 28 | 99.39 96 | 86.93 170 | 98.73 151 | 96.95 107 | 97.73 122 | 99.45 128 |
|
PVSNet_0 | | 88.03 19 | 91.80 209 | 90.27 221 | 96.38 174 | 98.27 134 | 90.46 260 | 99.94 45 | 99.61 16 | 93.99 100 | 86.26 271 | 97.39 185 | 71.13 300 | 99.89 68 | 98.77 52 | 67.05 325 | 98.79 183 |
|
PatchFormer-LS_test | | | 97.01 86 | 96.79 82 | 97.69 137 | 98.26 135 | 94.80 163 | 98.66 248 | 98.13 159 | 93.70 112 | 97.86 100 | 98.80 142 | 95.54 34 | 98.67 155 | 94.12 149 | 96.00 154 | 99.60 108 |
|
DWT-MVSNet_test | | | 97.31 76 | 97.19 69 | 97.66 138 | 98.24 136 | 94.67 167 | 98.86 233 | 98.20 149 | 93.60 115 | 98.09 94 | 98.89 125 | 97.51 5 | 98.78 148 | 94.04 150 | 97.28 133 | 99.55 116 |
|
UA-Net | | | 96.54 105 | 95.96 106 | 98.27 119 | 98.23 137 | 95.71 143 | 98.00 284 | 98.45 105 | 93.72 111 | 98.41 82 | 99.27 101 | 88.71 155 | 99.66 112 | 91.19 189 | 97.69 123 | 99.44 130 |
|
GG-mvs-BLEND | | | | | 98.54 98 | 98.21 138 | 98.01 63 | 93.87 324 | 98.52 90 | | 97.92 98 | 97.92 177 | 99.02 2 | 97.94 209 | 98.17 71 | 99.58 82 | 99.67 96 |
|
mvs_anonymous | | | 95.65 138 | 95.03 142 | 97.53 141 | 98.19 139 | 95.74 140 | 99.33 184 | 97.49 214 | 90.87 199 | 90.47 199 | 97.10 192 | 88.23 158 | 97.16 241 | 95.92 118 | 97.66 125 | 99.68 95 |
|
MVS_Test | | | 96.46 114 | 95.74 121 | 98.61 91 | 98.18 140 | 97.23 94 | 99.31 185 | 97.15 241 | 91.07 195 | 98.84 64 | 97.05 196 | 88.17 159 | 98.97 141 | 94.39 141 | 97.50 127 | 99.61 106 |
|
BH-RMVSNet | | | 95.18 145 | 94.31 153 | 97.80 133 | 98.17 141 | 95.23 156 | 99.76 115 | 97.53 208 | 92.52 152 | 94.27 171 | 99.25 104 | 76.84 267 | 98.80 146 | 90.89 197 | 99.54 84 | 99.35 145 |
|
RPSCF | | | 91.80 209 | 92.79 182 | 88.83 307 | 98.15 142 | 69.87 330 | 98.11 280 | 96.60 286 | 83.93 291 | 94.33 170 | 99.27 101 | 79.60 245 | 99.46 126 | 91.99 181 | 93.16 203 | 97.18 199 |
|
diffmvs | | | 95.25 144 | 94.26 154 | 98.23 120 | 98.13 143 | 96.59 113 | 99.12 200 | 97.18 237 | 85.78 273 | 97.64 102 | 96.70 208 | 85.92 178 | 98.87 143 | 90.40 204 | 97.45 128 | 99.24 158 |
|
IS-MVSNet | | | 96.29 124 | 95.90 111 | 97.45 145 | 98.13 143 | 94.80 163 | 99.08 205 | 97.61 201 | 92.02 169 | 95.54 146 | 98.96 121 | 90.64 133 | 98.08 200 | 93.73 160 | 97.41 131 | 99.47 127 |
|
ab-mvs | | | 94.69 157 | 93.42 172 | 98.51 100 | 98.07 145 | 96.26 121 | 96.49 305 | 98.68 63 | 90.31 207 | 94.54 165 | 97.00 198 | 76.30 272 | 99.71 104 | 95.98 117 | 93.38 200 | 99.56 115 |
|
XVG-OURS-SEG-HR | | | 94.79 153 | 94.70 147 | 95.08 198 | 98.05 146 | 89.19 273 | 99.08 205 | 97.54 206 | 93.66 113 | 94.87 163 | 99.58 82 | 78.78 255 | 99.79 89 | 97.31 96 | 93.40 199 | 96.25 204 |
|
XVG-OURS | | | 94.82 152 | 94.74 146 | 95.06 199 | 98.00 147 | 89.19 273 | 99.08 205 | 97.55 204 | 94.10 93 | 94.71 164 | 99.62 80 | 80.51 237 | 99.74 100 | 96.04 116 | 93.06 204 | 96.25 204 |
|
dp | | | 95.05 149 | 94.43 151 | 96.91 158 | 97.99 148 | 92.73 214 | 96.29 309 | 97.98 169 | 89.70 216 | 95.93 136 | 94.67 276 | 93.83 83 | 98.45 173 | 86.91 251 | 96.53 148 | 99.54 120 |
|
tpmrst | | | 96.27 126 | 95.98 103 | 97.13 154 | 97.96 149 | 93.15 204 | 96.34 308 | 98.17 151 | 92.07 166 | 98.71 71 | 95.12 253 | 93.91 79 | 98.73 151 | 94.91 131 | 96.62 146 | 99.50 125 |
|
TR-MVS | | | 94.54 161 | 93.56 168 | 97.49 143 | 97.96 149 | 94.34 171 | 98.71 240 | 97.51 212 | 90.30 208 | 94.51 167 | 98.69 149 | 75.56 277 | 98.77 149 | 92.82 172 | 95.99 155 | 99.35 145 |
|
Vis-MVSNet (Re-imp) | | | 96.32 121 | 95.98 103 | 97.35 151 | 97.93 151 | 94.82 162 | 99.47 169 | 98.15 156 | 91.83 173 | 95.09 161 | 99.11 110 | 91.37 122 | 97.47 219 | 93.47 162 | 97.43 129 | 99.74 87 |
|
MDTV_nov1_ep13 | | | | 95.69 122 | | 97.90 152 | 94.15 174 | 95.98 314 | 98.44 106 | 93.12 123 | 97.98 97 | 95.74 229 | 95.10 42 | 98.58 163 | 90.02 209 | 96.92 144 | |
|
Fast-Effi-MVS+ | | | 95.02 150 | 94.19 155 | 97.52 142 | 97.88 153 | 94.55 168 | 99.97 12 | 97.08 244 | 88.85 230 | 94.47 168 | 97.96 176 | 84.59 189 | 98.41 176 | 89.84 210 | 97.10 140 | 99.59 110 |
|
ADS-MVSNet2 | | | 93.80 175 | 93.88 161 | 93.55 254 | 97.87 154 | 85.94 296 | 94.24 320 | 96.84 277 | 90.07 210 | 96.43 127 | 94.48 280 | 90.29 136 | 95.37 298 | 87.44 237 | 97.23 136 | 99.36 143 |
|
ADS-MVSNet | | | 94.79 153 | 94.02 158 | 97.11 156 | 97.87 154 | 93.79 181 | 94.24 320 | 98.16 154 | 90.07 210 | 96.43 127 | 94.48 280 | 90.29 136 | 98.19 197 | 87.44 237 | 97.23 136 | 99.36 143 |
|
Effi-MVS+ | | | 96.30 123 | 95.69 122 | 98.16 121 | 97.85 156 | 96.26 121 | 97.41 291 | 97.21 235 | 90.37 205 | 98.65 74 | 98.58 158 | 86.61 173 | 98.70 154 | 97.11 101 | 97.37 132 | 99.52 122 |
|
tpmp4_e23 | | | 95.15 148 | 94.69 148 | 96.55 169 | 97.84 157 | 91.77 238 | 97.10 297 | 97.91 176 | 88.33 238 | 97.19 111 | 95.06 257 | 93.92 77 | 98.51 167 | 89.64 212 | 95.19 170 | 99.37 142 |
|
PatchmatchNet | | | 95.94 131 | 95.45 130 | 97.39 149 | 97.83 158 | 94.41 170 | 96.05 313 | 98.40 123 | 92.86 127 | 97.09 114 | 95.28 250 | 94.21 71 | 98.07 202 | 89.26 221 | 98.11 116 | 99.70 92 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
cascas | | | 94.64 159 | 93.61 163 | 97.74 136 | 97.82 159 | 96.26 121 | 99.96 19 | 97.78 188 | 85.76 274 | 94.00 173 | 97.54 181 | 76.95 266 | 99.21 134 | 97.23 98 | 95.43 167 | 97.76 197 |
|
1112_ss | | | 96.01 130 | 95.20 138 | 98.42 111 | 97.80 160 | 96.41 117 | 99.65 145 | 96.66 283 | 92.71 137 | 92.88 183 | 99.40 94 | 92.16 111 | 99.30 132 | 91.92 182 | 93.66 196 | 99.55 116 |
|
Test_1112_low_res | | | 95.72 134 | 94.83 144 | 98.42 111 | 97.79 161 | 96.41 117 | 99.65 145 | 96.65 284 | 92.70 138 | 92.86 184 | 96.13 224 | 92.15 112 | 99.30 132 | 91.88 183 | 93.64 197 | 99.55 116 |
|
Effi-MVS+-dtu | | | 94.53 163 | 95.30 135 | 92.22 281 | 97.77 162 | 82.54 312 | 99.59 153 | 97.06 245 | 94.92 69 | 95.29 149 | 95.37 243 | 85.81 179 | 97.89 210 | 94.80 133 | 97.07 141 | 96.23 206 |
|
mvs-test1 | | | 95.53 139 | 95.97 105 | 94.20 234 | 97.77 162 | 85.44 301 | 99.95 31 | 97.06 245 | 94.92 69 | 96.58 122 | 98.72 148 | 85.81 179 | 98.98 140 | 94.80 133 | 98.11 116 | 98.18 189 |
|
tpm cat1 | | | 93.51 181 | 92.52 187 | 96.47 170 | 97.77 162 | 91.47 249 | 96.13 311 | 98.06 163 | 80.98 311 | 92.91 182 | 93.78 292 | 89.66 139 | 98.87 143 | 87.03 247 | 96.39 150 | 99.09 175 |
|
xiu_mvs_v1_base_debu | | | 97.43 71 | 97.06 72 | 98.55 95 | 97.74 165 | 98.14 57 | 99.31 185 | 97.86 182 | 96.43 31 | 99.62 22 | 99.69 71 | 85.56 182 | 99.68 108 | 99.05 35 | 98.31 112 | 97.83 194 |
|
xiu_mvs_v1_base | | | 97.43 71 | 97.06 72 | 98.55 95 | 97.74 165 | 98.14 57 | 99.31 185 | 97.86 182 | 96.43 31 | 99.62 22 | 99.69 71 | 85.56 182 | 99.68 108 | 99.05 35 | 98.31 112 | 97.83 194 |
|
xiu_mvs_v1_base_debi | | | 97.43 71 | 97.06 72 | 98.55 95 | 97.74 165 | 98.14 57 | 99.31 185 | 97.86 182 | 96.43 31 | 99.62 22 | 99.69 71 | 85.56 182 | 99.68 108 | 99.05 35 | 98.31 112 | 97.83 194 |
|
EPP-MVSNet | | | 96.69 101 | 96.60 87 | 96.96 157 | 97.74 165 | 93.05 207 | 99.37 180 | 98.56 83 | 88.75 231 | 95.83 141 | 99.01 116 | 96.01 24 | 98.56 164 | 96.92 108 | 97.20 138 | 99.25 155 |
|
gg-mvs-nofinetune | | | 93.51 181 | 91.86 196 | 98.47 106 | 97.72 169 | 97.96 64 | 92.62 329 | 98.51 96 | 74.70 327 | 97.33 108 | 69.59 343 | 98.91 3 | 97.79 212 | 97.77 89 | 99.56 83 | 99.67 96 |
|
IB-MVS | | 92.85 6 | 94.99 151 | 93.94 159 | 98.16 121 | 97.72 169 | 95.69 145 | 99.99 3 | 98.81 55 | 94.28 88 | 92.70 185 | 96.90 200 | 95.08 43 | 99.17 136 | 96.07 115 | 73.88 315 | 99.60 108 |
Christian Sormann, Mattia Rossi, Andreas Kuhn and Friedrich Fraundorfer: IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions. BMVC 2021 |
Vis-MVSNet | | | 95.72 134 | 95.15 140 | 97.45 145 | 97.62 171 | 94.28 172 | 99.28 190 | 98.24 143 | 94.27 89 | 96.84 117 | 98.94 124 | 79.39 246 | 98.76 150 | 93.25 165 | 98.49 107 | 99.30 150 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
testpf | | | 89.10 262 | 88.73 254 | 90.24 298 | 97.59 172 | 83.48 309 | 74.22 347 | 97.39 224 | 79.66 315 | 89.64 222 | 93.92 288 | 86.38 174 | 95.76 294 | 85.42 262 | 94.31 183 | 91.49 309 |
|
LCM-MVSNet-Re | | | 92.31 201 | 92.60 185 | 91.43 288 | 97.53 173 | 79.27 326 | 99.02 217 | 91.83 340 | 92.07 166 | 80.31 296 | 94.38 283 | 83.50 196 | 95.48 296 | 97.22 99 | 97.58 126 | 99.54 120 |
|
GBi-Net | | | 90.88 231 | 89.82 233 | 94.08 237 | 97.53 173 | 91.97 229 | 98.43 261 | 96.95 266 | 87.05 257 | 89.68 218 | 94.72 272 | 71.34 297 | 96.11 286 | 87.01 248 | 85.65 244 | 94.17 237 |
|
test1 | | | 90.88 231 | 89.82 233 | 94.08 237 | 97.53 173 | 91.97 229 | 98.43 261 | 96.95 266 | 87.05 257 | 89.68 218 | 94.72 272 | 71.34 297 | 96.11 286 | 87.01 248 | 85.65 244 | 94.17 237 |
|
FMVSNet2 | | | 91.02 228 | 89.56 237 | 95.41 192 | 97.53 173 | 95.74 140 | 98.98 219 | 97.41 222 | 87.05 257 | 88.43 243 | 95.00 262 | 71.34 297 | 96.24 284 | 85.12 265 | 85.21 249 | 94.25 234 |
|
CDS-MVSNet | | | 96.34 120 | 96.07 98 | 97.13 154 | 97.37 177 | 94.96 159 | 99.53 162 | 97.91 176 | 91.55 179 | 95.37 148 | 98.32 168 | 95.05 45 | 97.13 247 | 93.80 157 | 95.75 162 | 99.30 150 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
TESTMET0.1,1 | | | 96.74 98 | 96.26 95 | 98.16 121 | 97.36 178 | 96.48 115 | 99.96 19 | 98.29 138 | 91.93 170 | 95.77 142 | 98.07 173 | 95.54 34 | 98.29 190 | 90.55 200 | 98.89 100 | 99.70 92 |
|
MVSFormer | | | 96.94 88 | 96.60 87 | 97.95 130 | 97.28 179 | 97.70 72 | 99.55 159 | 97.27 232 | 91.17 192 | 99.43 37 | 99.54 86 | 90.92 130 | 96.89 263 | 94.67 137 | 99.62 77 | 99.25 155 |
|
lupinMVS | | | 97.85 60 | 97.60 59 | 98.62 90 | 97.28 179 | 97.70 72 | 99.99 3 | 97.55 204 | 95.50 60 | 99.43 37 | 99.67 75 | 90.92 130 | 98.71 153 | 98.40 67 | 99.62 77 | 99.45 128 |
|
Patchmatch-test1 | | | 94.39 166 | 93.46 170 | 97.17 153 | 97.10 181 | 94.44 169 | 98.86 233 | 98.32 135 | 93.30 121 | 96.17 133 | 95.38 241 | 76.48 271 | 97.34 225 | 88.12 231 | 97.43 129 | 99.74 87 |
|
TAMVS | | | 95.85 132 | 95.58 128 | 96.65 168 | 97.07 182 | 93.50 188 | 99.17 198 | 97.82 186 | 91.39 185 | 95.02 162 | 98.01 174 | 92.20 110 | 97.30 231 | 93.75 159 | 95.83 160 | 99.14 170 |
|
Fast-Effi-MVS+-dtu | | | 93.72 178 | 93.86 162 | 93.29 257 | 97.06 183 | 86.16 294 | 99.80 100 | 96.83 278 | 92.66 141 | 92.58 186 | 97.83 178 | 81.39 223 | 97.67 215 | 89.75 211 | 96.87 145 | 96.05 208 |
|
CostFormer | | | 96.10 127 | 95.88 112 | 96.78 162 | 97.03 184 | 92.55 220 | 97.08 298 | 97.83 185 | 90.04 212 | 98.72 70 | 94.89 268 | 95.01 47 | 98.29 190 | 96.54 111 | 95.77 161 | 99.50 125 |
|
test-LLR | | | 96.47 113 | 96.04 99 | 97.78 134 | 97.02 185 | 95.44 148 | 99.96 19 | 98.21 146 | 94.07 95 | 95.55 144 | 96.38 216 | 93.90 80 | 98.27 193 | 90.42 202 | 98.83 102 | 99.64 102 |
|
test-mter | | | 96.39 119 | 95.93 108 | 97.78 134 | 97.02 185 | 95.44 148 | 99.96 19 | 98.21 146 | 91.81 174 | 95.55 144 | 96.38 216 | 95.17 40 | 98.27 193 | 90.42 202 | 98.83 102 | 99.64 102 |
|
gm-plane-assit | | | | | | 96.97 187 | 93.76 185 | | | 91.47 182 | | 98.96 121 | | 98.79 147 | 94.92 129 | | |
|
QAPM | | | 95.40 142 | 94.17 156 | 99.10 56 | 96.92 188 | 97.71 70 | 99.40 175 | 98.68 63 | 89.31 218 | 88.94 237 | 98.89 125 | 82.48 201 | 99.96 42 | 93.12 171 | 99.83 61 | 99.62 104 |
|
tpm2 | | | 95.47 141 | 95.18 139 | 96.35 175 | 96.91 189 | 91.70 243 | 96.96 301 | 97.93 174 | 88.04 242 | 98.44 81 | 95.40 238 | 93.32 91 | 97.97 205 | 94.00 151 | 95.61 164 | 99.38 140 |
|
FMVSNet5 | | | 88.32 268 | 87.47 268 | 90.88 291 | 96.90 190 | 88.39 284 | 97.28 295 | 95.68 301 | 82.60 297 | 84.67 280 | 92.40 304 | 79.83 244 | 91.16 329 | 76.39 315 | 81.51 264 | 93.09 290 |
|
3Dnovator+ | | 91.53 11 | 96.31 122 | 95.24 136 | 99.52 19 | 96.88 191 | 98.64 38 | 99.72 129 | 98.24 143 | 95.27 65 | 88.42 245 | 98.98 119 | 82.76 200 | 99.94 58 | 97.10 102 | 99.83 61 | 99.96 57 |
|
Patchmatch-test | | | 92.65 196 | 91.50 200 | 96.10 180 | 96.85 192 | 90.49 259 | 91.50 334 | 97.19 236 | 82.76 296 | 90.23 200 | 95.59 234 | 95.02 46 | 98.00 204 | 77.41 310 | 96.98 143 | 99.82 78 |
|
MVS | | | 96.60 104 | 95.56 129 | 99.72 4 | 96.85 192 | 99.22 8 | 98.31 269 | 98.94 37 | 91.57 178 | 90.90 195 | 99.61 81 | 86.66 172 | 99.96 42 | 97.36 95 | 99.88 56 | 99.99 11 |
|
3Dnovator | | 91.47 12 | 96.28 125 | 95.34 134 | 99.08 58 | 96.82 194 | 97.47 81 | 99.45 172 | 98.81 55 | 95.52 59 | 89.39 227 | 99.00 118 | 81.97 210 | 99.95 50 | 97.27 97 | 99.83 61 | 99.84 76 |
|
EI-MVSNet | | | 93.73 177 | 93.40 175 | 94.74 215 | 96.80 195 | 92.69 215 | 99.06 211 | 97.67 194 | 88.96 226 | 91.39 191 | 99.02 114 | 88.75 154 | 97.30 231 | 91.07 191 | 87.85 231 | 94.22 235 |
|
CVMVSNet | | | 94.68 158 | 94.94 143 | 93.89 247 | 96.80 195 | 86.92 293 | 99.06 211 | 98.98 35 | 94.45 81 | 94.23 172 | 99.02 114 | 85.60 181 | 95.31 299 | 90.91 196 | 95.39 168 | 99.43 131 |
|
IterMVS-LS | | | 92.69 194 | 92.11 192 | 94.43 229 | 96.80 195 | 92.74 213 | 99.45 172 | 96.89 273 | 88.98 224 | 89.65 221 | 95.38 241 | 88.77 153 | 96.34 280 | 90.98 194 | 82.04 261 | 94.22 235 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
IterMVS | | | 90.91 230 | 90.17 225 | 93.12 259 | 96.78 198 | 90.42 261 | 98.89 227 | 97.05 249 | 89.03 222 | 86.49 266 | 95.42 237 | 76.59 269 | 95.02 302 | 87.22 244 | 84.09 253 | 93.93 262 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
1314 | | | 96.84 92 | 95.96 106 | 99.48 24 | 96.74 199 | 98.52 46 | 98.31 269 | 98.86 52 | 95.82 48 | 89.91 209 | 98.98 119 | 87.49 163 | 99.96 42 | 97.80 86 | 99.73 70 | 99.96 57 |
|
semantic-postprocess | | | | | 92.93 263 | 96.72 200 | 89.96 268 | | 96.99 259 | 88.95 227 | 86.63 263 | 95.67 231 | 76.50 270 | 95.00 303 | 87.04 246 | 84.04 256 | 93.84 270 |
|
MVS-HIRNet | | | 86.22 281 | 83.19 296 | 95.31 193 | 96.71 201 | 90.29 262 | 92.12 331 | 97.33 229 | 62.85 338 | 86.82 261 | 70.37 342 | 69.37 305 | 97.49 218 | 75.12 316 | 97.99 121 | 98.15 190 |
|
VDDNet | | | 93.12 186 | 91.91 195 | 96.76 163 | 96.67 202 | 92.65 218 | 98.69 242 | 98.21 146 | 82.81 295 | 97.75 101 | 99.28 100 | 61.57 326 | 99.48 125 | 98.09 76 | 94.09 187 | 98.15 190 |
|
MIMVSNet | | | 90.30 244 | 88.67 255 | 95.17 197 | 96.45 203 | 91.64 245 | 92.39 330 | 97.15 241 | 85.99 270 | 90.50 198 | 93.19 300 | 66.95 313 | 94.86 306 | 82.01 286 | 93.43 198 | 99.01 178 |
|
CR-MVSNet | | | 93.45 184 | 92.62 184 | 95.94 182 | 96.29 204 | 92.66 216 | 92.01 332 | 96.23 291 | 92.62 144 | 96.94 115 | 93.31 298 | 91.04 128 | 96.03 290 | 79.23 300 | 95.96 156 | 99.13 172 |
|
RPMNet | | | 89.39 258 | 87.20 270 | 95.94 182 | 96.29 204 | 92.66 216 | 92.01 332 | 97.63 196 | 70.19 335 | 96.94 115 | 85.87 335 | 87.25 166 | 96.03 290 | 62.69 332 | 95.96 156 | 99.13 172 |
|
Patchmtry | | | 89.70 253 | 88.49 256 | 93.33 256 | 96.24 206 | 89.94 271 | 91.37 335 | 96.23 291 | 78.22 318 | 87.69 251 | 93.31 298 | 91.04 128 | 96.03 290 | 80.18 294 | 82.10 260 | 94.02 246 |
|
JIA-IIPM | | | 91.76 212 | 90.70 209 | 94.94 206 | 96.11 207 | 87.51 289 | 93.16 327 | 98.13 159 | 75.79 324 | 97.58 104 | 77.68 339 | 92.84 99 | 97.97 205 | 88.47 227 | 96.54 147 | 99.33 147 |
|
OpenMVS | | 90.15 15 | 94.77 155 | 93.59 166 | 98.33 117 | 96.07 208 | 97.48 80 | 99.56 157 | 98.57 81 | 90.46 204 | 86.51 265 | 98.95 123 | 78.57 257 | 99.94 58 | 93.86 152 | 99.74 69 | 97.57 198 |
|
PAPM | | | 98.60 25 | 98.42 25 | 99.14 50 | 96.05 209 | 98.96 13 | 99.90 59 | 99.35 26 | 96.68 28 | 98.35 86 | 99.66 77 | 96.45 21 | 98.51 167 | 99.45 24 | 99.89 54 | 99.96 57 |
|
CLD-MVS | | | 94.06 170 | 93.90 160 | 94.55 224 | 96.02 210 | 90.69 256 | 99.98 6 | 97.72 191 | 96.62 30 | 91.05 194 | 98.85 135 | 77.21 263 | 98.47 169 | 98.11 74 | 89.51 211 | 94.48 214 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
PatchT | | | 90.38 241 | 88.75 253 | 95.25 194 | 95.99 211 | 90.16 264 | 91.22 336 | 97.54 206 | 76.80 321 | 97.26 109 | 86.01 334 | 91.88 116 | 96.07 289 | 66.16 329 | 95.91 158 | 99.51 123 |
|
ACMH+ | | 89.98 16 | 90.35 242 | 89.54 238 | 92.78 266 | 95.99 211 | 86.12 295 | 98.81 235 | 97.18 237 | 89.38 217 | 83.14 287 | 97.76 179 | 68.42 309 | 98.43 174 | 89.11 222 | 86.05 243 | 93.78 273 |
|
DeepMVS_CX | | | | | 82.92 319 | 95.98 213 | 58.66 343 | | 96.01 296 | 92.72 136 | 78.34 303 | 95.51 235 | 58.29 332 | 98.08 200 | 82.57 282 | 85.29 247 | 92.03 303 |
|
ACMP | | 92.05 9 | 92.74 192 | 92.42 189 | 93.73 248 | 95.91 214 | 88.72 277 | 99.81 97 | 97.53 208 | 94.13 91 | 87.00 258 | 98.23 169 | 74.07 288 | 98.47 169 | 96.22 114 | 88.86 218 | 93.99 254 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
HQP-NCC | | | | | | 95.78 215 | | 99.87 71 | | 96.82 21 | 93.37 175 | | | | | | |
|
ACMP_Plane | | | | | | 95.78 215 | | 99.87 71 | | 96.82 21 | 93.37 175 | | | | | | |
|
HQP-MVS | | | 94.61 160 | 94.50 150 | 94.92 208 | 95.78 215 | 91.85 234 | 99.87 71 | 97.89 178 | 96.82 21 | 93.37 175 | 98.65 152 | 80.65 235 | 98.39 180 | 97.92 84 | 89.60 206 | 94.53 210 |
|
NP-MVS | | | | | | 95.77 218 | 91.79 236 | | | | | 98.65 152 | | | | | |
|
plane_prior6 | | | | | | 95.76 219 | 91.72 242 | | | | | | 80.47 239 | | | | |
|
ACMM | | 91.95 10 | 92.88 190 | 92.52 187 | 93.98 244 | 95.75 220 | 89.08 275 | 99.77 109 | 97.52 210 | 93.00 125 | 89.95 208 | 97.99 175 | 76.17 274 | 98.46 172 | 93.63 161 | 88.87 217 | 94.39 222 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
GA-MVS | | | 93.83 172 | 92.84 180 | 96.80 161 | 95.73 221 | 93.57 187 | 99.88 66 | 97.24 234 | 92.57 150 | 92.92 181 | 96.66 209 | 78.73 256 | 97.67 215 | 87.75 234 | 94.06 194 | 99.17 163 |
|
plane_prior1 | | | | | | 95.73 221 | | | | | | | | | | | |
|
jason | | | 97.24 79 | 96.86 78 | 98.38 116 | 95.73 221 | 97.32 92 | 99.97 12 | 97.40 223 | 95.34 63 | 98.60 77 | 99.54 86 | 87.70 161 | 98.56 164 | 97.94 83 | 99.47 88 | 99.25 155 |
jason: jason. |
HQP_MVS | | | 94.49 164 | 94.36 152 | 94.87 211 | 95.71 224 | 91.74 239 | 99.84 90 | 97.87 180 | 96.38 34 | 93.01 179 | 98.59 156 | 80.47 239 | 98.37 185 | 97.79 87 | 89.55 209 | 94.52 212 |
|
plane_prior7 | | | | | | 95.71 224 | 91.59 247 | | | | | | | | | | |
|
ITE_SJBPF | | | | | 92.38 277 | 95.69 226 | 85.14 302 | | 95.71 300 | 92.81 131 | 89.33 230 | 98.11 171 | 70.23 303 | 98.42 175 | 85.91 259 | 88.16 229 | 93.59 280 |
|
ACMH | | 89.72 17 | 90.64 236 | 89.63 235 | 93.66 252 | 95.64 227 | 88.64 280 | 98.55 252 | 97.45 216 | 89.03 222 | 81.62 292 | 97.61 180 | 69.75 304 | 98.41 176 | 89.37 219 | 87.62 235 | 93.92 263 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
FMVSNet1 | | | 88.50 267 | 86.64 271 | 94.08 237 | 95.62 228 | 91.97 229 | 98.43 261 | 96.95 266 | 83.00 294 | 86.08 273 | 94.72 272 | 59.09 331 | 96.11 286 | 81.82 288 | 84.07 254 | 94.17 237 |
|
LPG-MVS_test | | | 92.96 188 | 92.71 183 | 93.71 250 | 95.43 229 | 88.67 278 | 99.75 116 | 97.62 198 | 92.81 131 | 90.05 203 | 98.49 161 | 75.24 280 | 98.40 178 | 95.84 121 | 89.12 213 | 94.07 243 |
|
LGP-MVS_train | | | | | 93.71 250 | 95.43 229 | 88.67 278 | | 97.62 198 | 92.81 131 | 90.05 203 | 98.49 161 | 75.24 280 | 98.40 178 | 95.84 121 | 89.12 213 | 94.07 243 |
|
tpm | | | 93.70 179 | 93.41 174 | 94.58 222 | 95.36 231 | 87.41 291 | 97.01 299 | 96.90 272 | 90.85 200 | 96.72 121 | 94.14 287 | 90.40 134 | 96.84 266 | 90.75 198 | 88.54 224 | 99.51 123 |
|
VPA-MVSNet | | | 92.70 193 | 91.55 199 | 96.16 178 | 95.09 232 | 96.20 126 | 98.88 228 | 99.00 34 | 91.02 197 | 91.82 189 | 95.29 249 | 76.05 276 | 97.96 207 | 95.62 124 | 81.19 266 | 94.30 230 |
|
LP | | | 86.76 274 | 84.85 278 | 92.50 272 | 95.08 233 | 85.89 297 | 89.97 337 | 96.97 264 | 75.28 326 | 84.97 279 | 90.68 310 | 80.78 232 | 95.13 301 | 61.64 334 | 88.31 227 | 96.46 203 |
|
LTVRE_ROB | | 88.28 18 | 90.29 245 | 89.05 248 | 94.02 240 | 95.08 233 | 90.15 265 | 97.19 296 | 97.43 218 | 84.91 283 | 83.99 283 | 97.06 195 | 74.00 289 | 98.28 192 | 84.08 271 | 87.71 233 | 93.62 279 |
Andreas Kuhn, Heiko Hirschmüller, Daniel Scharstein, Helmut Mayer: A TV Prior for High-Quality Scalable Multi-View Stereo Reconstruction. International Journal of Computer Vision 2016 |
TinyColmap | | | 87.87 271 | 86.51 272 | 91.94 284 | 95.05 235 | 85.57 299 | 97.65 288 | 94.08 329 | 84.40 289 | 81.82 291 | 96.85 204 | 62.14 325 | 98.33 187 | 80.25 293 | 86.37 242 | 91.91 305 |
|
test0.0.03 1 | | | 93.86 171 | 93.61 163 | 94.64 219 | 95.02 236 | 92.18 227 | 99.93 50 | 98.58 79 | 94.07 95 | 87.96 249 | 98.50 160 | 93.90 80 | 94.96 304 | 81.33 289 | 93.17 202 | 96.78 200 |
|
UniMVSNet (Re) | | | 93.07 187 | 92.13 191 | 95.88 184 | 94.84 237 | 96.24 125 | 99.88 66 | 98.98 35 | 92.49 154 | 89.25 231 | 95.40 238 | 87.09 168 | 97.14 245 | 93.13 170 | 78.16 294 | 94.26 232 |
|
USDC | | | 90.00 251 | 88.96 249 | 93.10 260 | 94.81 238 | 88.16 286 | 98.71 240 | 95.54 306 | 93.66 113 | 83.75 285 | 97.20 189 | 65.58 316 | 98.31 189 | 83.96 274 | 87.49 237 | 92.85 296 |
|
VPNet | | | 91.81 207 | 90.46 213 | 95.85 186 | 94.74 239 | 95.54 147 | 98.98 219 | 98.59 78 | 92.14 163 | 90.77 197 | 97.44 183 | 68.73 307 | 97.54 217 | 94.89 132 | 77.89 296 | 94.46 215 |
|
FIs | | | 94.10 169 | 93.43 171 | 96.11 179 | 94.70 240 | 96.82 107 | 99.58 154 | 98.93 40 | 92.54 151 | 89.34 229 | 97.31 186 | 87.62 162 | 97.10 250 | 94.22 148 | 86.58 240 | 94.40 221 |
|
UniMVSNet_NR-MVSNet | | | 92.95 189 | 92.11 192 | 95.49 189 | 94.61 241 | 95.28 154 | 99.83 94 | 99.08 31 | 91.49 180 | 89.21 233 | 96.86 203 | 87.14 167 | 96.73 270 | 93.20 166 | 77.52 300 | 94.46 215 |
|
WR-MVS | | | 92.31 201 | 91.25 203 | 95.48 191 | 94.45 242 | 95.29 153 | 99.60 152 | 98.68 63 | 90.10 209 | 88.07 248 | 96.89 201 | 80.68 234 | 96.80 269 | 93.14 169 | 79.67 285 | 94.36 224 |
|
nrg030 | | | 93.51 181 | 92.53 186 | 96.45 171 | 94.36 243 | 97.20 95 | 99.81 97 | 97.16 240 | 91.60 177 | 89.86 212 | 97.46 182 | 86.37 175 | 97.68 214 | 95.88 119 | 80.31 276 | 94.46 215 |
|
tfpnnormal | | | 89.29 260 | 87.61 266 | 94.34 231 | 94.35 244 | 94.13 175 | 98.95 223 | 98.94 37 | 83.94 290 | 84.47 281 | 95.51 235 | 74.84 283 | 97.39 221 | 77.05 313 | 80.41 274 | 91.48 310 |
|
FC-MVSNet-test | | | 93.81 174 | 93.15 178 | 95.80 187 | 94.30 245 | 96.20 126 | 99.42 174 | 98.89 50 | 92.33 157 | 89.03 236 | 97.27 188 | 87.39 165 | 96.83 267 | 93.20 166 | 86.48 241 | 94.36 224 |
|
MS-PatchMatch | | | 90.65 235 | 90.30 218 | 91.71 287 | 94.22 246 | 85.50 300 | 98.24 274 | 97.70 192 | 88.67 232 | 86.42 268 | 96.37 218 | 67.82 311 | 98.03 203 | 83.62 276 | 99.62 77 | 91.60 308 |
|
WR-MVS_H | | | 91.30 221 | 90.35 216 | 94.15 235 | 94.17 247 | 92.62 219 | 99.17 198 | 98.94 37 | 88.87 229 | 86.48 267 | 94.46 282 | 84.36 191 | 96.61 273 | 88.19 228 | 78.51 290 | 93.21 289 |
|
DU-MVS | | | 92.46 199 | 91.45 202 | 95.49 189 | 94.05 248 | 95.28 154 | 99.81 97 | 98.74 59 | 92.25 158 | 89.21 233 | 96.64 211 | 81.66 217 | 96.73 270 | 93.20 166 | 77.52 300 | 94.46 215 |
|
NR-MVSNet | | | 91.56 214 | 90.22 223 | 95.60 188 | 94.05 248 | 95.76 139 | 98.25 273 | 98.70 61 | 91.16 194 | 80.78 295 | 96.64 211 | 83.23 199 | 96.57 274 | 91.41 187 | 77.73 298 | 94.46 215 |
|
CP-MVSNet | | | 91.23 224 | 90.22 223 | 94.26 232 | 93.96 250 | 92.39 223 | 99.09 203 | 98.57 81 | 88.95 227 | 86.42 268 | 96.57 213 | 79.19 250 | 96.37 278 | 90.29 206 | 78.95 287 | 94.02 246 |
|
XXY-MVS | | | 91.82 206 | 90.46 213 | 95.88 184 | 93.91 251 | 95.40 151 | 98.87 231 | 97.69 193 | 88.63 234 | 87.87 250 | 97.08 193 | 74.38 287 | 97.89 210 | 91.66 186 | 84.07 254 | 94.35 227 |
|
PS-CasMVS | | | 90.63 237 | 89.51 240 | 93.99 243 | 93.83 252 | 91.70 243 | 98.98 219 | 98.52 90 | 88.48 235 | 86.15 272 | 96.53 215 | 75.46 278 | 96.31 281 | 88.83 224 | 78.86 289 | 93.95 260 |
|
test_0402 | | | 85.58 288 | 83.94 291 | 90.50 295 | 93.81 253 | 85.04 303 | 98.55 252 | 95.20 320 | 76.01 322 | 79.72 299 | 95.13 252 | 64.15 321 | 96.26 283 | 66.04 330 | 86.88 239 | 90.21 321 |
|
XVG-ACMP-BASELINE | | | 91.22 225 | 90.75 208 | 92.63 268 | 93.73 254 | 85.61 298 | 98.52 256 | 97.44 217 | 92.77 135 | 89.90 210 | 96.85 204 | 66.64 314 | 98.39 180 | 92.29 175 | 88.61 222 | 93.89 266 |
|
TranMVSNet+NR-MVSNet | | | 91.68 213 | 90.61 210 | 94.87 211 | 93.69 255 | 93.98 177 | 99.69 132 | 98.65 66 | 91.03 196 | 88.44 242 | 96.83 207 | 80.05 243 | 96.18 285 | 90.26 207 | 76.89 307 | 94.45 220 |
|
v7 | | | 91.20 226 | 89.99 231 | 94.82 214 | 93.57 256 | 93.41 195 | 99.57 155 | 96.98 261 | 86.83 261 | 89.88 211 | 95.22 251 | 81.01 228 | 97.14 245 | 85.53 261 | 81.31 265 | 93.90 264 |
|
TransMVSNet (Re) | | | 87.25 272 | 85.28 276 | 93.16 258 | 93.56 257 | 91.03 251 | 98.54 254 | 94.05 330 | 83.69 292 | 81.09 294 | 96.16 222 | 75.32 279 | 96.40 277 | 76.69 314 | 68.41 322 | 92.06 302 |
|
v10 | | | 90.25 246 | 88.82 251 | 94.57 223 | 93.53 258 | 93.43 191 | 99.08 205 | 96.87 276 | 85.00 282 | 87.34 256 | 94.51 278 | 80.93 230 | 97.02 259 | 82.85 281 | 79.23 286 | 93.26 287 |
|
v1neww | | | 91.44 215 | 90.28 219 | 94.91 209 | 93.50 259 | 93.43 191 | 99.73 124 | 97.06 245 | 87.55 245 | 90.08 201 | 95.11 254 | 81.98 208 | 97.32 228 | 87.41 239 | 80.15 278 | 93.99 254 |
|
v7new | | | 91.44 215 | 90.28 219 | 94.91 209 | 93.50 259 | 93.43 191 | 99.73 124 | 97.06 245 | 87.55 245 | 90.08 201 | 95.11 254 | 81.98 208 | 97.32 228 | 87.41 239 | 80.15 278 | 93.99 254 |
|
testgi | | | 89.01 263 | 88.04 262 | 91.90 285 | 93.49 261 | 84.89 304 | 99.73 124 | 95.66 302 | 93.89 107 | 85.14 277 | 98.17 170 | 59.68 330 | 94.66 308 | 77.73 308 | 88.88 216 | 96.16 207 |
|
v16 | | | 86.52 276 | 84.49 280 | 92.60 270 | 93.45 262 | 93.31 200 | 98.60 251 | 95.52 308 | 82.30 300 | 74.59 317 | 87.70 320 | 81.95 212 | 94.18 310 | 79.93 297 | 66.38 327 | 90.30 318 |
|
v6 | | | 91.44 215 | 90.27 221 | 94.93 207 | 93.44 263 | 93.44 190 | 99.73 124 | 97.05 249 | 87.57 244 | 90.05 203 | 95.10 256 | 81.87 213 | 97.39 221 | 87.45 236 | 80.17 277 | 93.98 258 |
|
v8 | | | 90.54 239 | 89.17 244 | 94.66 218 | 93.43 264 | 93.40 198 | 99.20 195 | 96.94 269 | 85.76 274 | 87.56 252 | 94.51 278 | 81.96 211 | 97.19 239 | 84.94 267 | 78.25 293 | 93.38 285 |
|
V42 | | | 91.28 223 | 90.12 229 | 94.74 215 | 93.42 265 | 93.46 189 | 99.68 137 | 97.02 255 | 87.36 253 | 89.85 213 | 95.05 258 | 81.31 225 | 97.34 225 | 87.34 242 | 80.07 280 | 93.40 283 |
|
v18 | | | 86.59 275 | 84.57 279 | 92.65 267 | 93.41 266 | 93.43 191 | 98.69 242 | 95.55 305 | 82.44 298 | 74.71 315 | 87.68 321 | 82.11 205 | 94.21 309 | 80.14 295 | 66.37 328 | 90.32 317 |
|
pm-mvs1 | | | 89.36 259 | 87.81 264 | 94.01 241 | 93.40 267 | 91.93 232 | 98.62 249 | 96.48 290 | 86.25 268 | 83.86 284 | 96.14 223 | 73.68 290 | 97.04 254 | 86.16 257 | 75.73 311 | 93.04 292 |
|
v17 | | | 86.51 277 | 84.49 280 | 92.57 271 | 93.38 268 | 93.29 201 | 98.61 250 | 95.54 306 | 82.32 299 | 74.69 316 | 87.63 322 | 82.03 206 | 94.17 311 | 80.02 296 | 66.17 329 | 90.26 319 |
|
divwei89l23v2f112 | | | 91.37 218 | 90.15 226 | 95.00 202 | 93.35 269 | 93.78 184 | 99.78 104 | 97.05 249 | 87.54 247 | 89.73 217 | 94.89 268 | 82.24 203 | 97.21 237 | 86.91 251 | 79.90 284 | 94.00 251 |
|
v1 | | | 91.36 219 | 90.14 227 | 95.04 200 | 93.35 269 | 93.80 180 | 99.77 109 | 97.05 249 | 87.53 248 | 89.77 215 | 94.91 266 | 81.99 207 | 97.33 227 | 86.90 253 | 79.98 283 | 94.00 251 |
|
v1141 | | | 91.36 219 | 90.14 227 | 95.00 202 | 93.33 271 | 93.79 181 | 99.78 104 | 97.05 249 | 87.52 249 | 89.75 216 | 94.89 268 | 82.13 204 | 97.21 237 | 86.84 254 | 80.00 282 | 94.00 251 |
|
V14 | | | 86.22 281 | 84.15 284 | 92.41 276 | 93.30 272 | 93.16 203 | 98.47 258 | 95.47 309 | 82.10 303 | 74.27 319 | 87.41 323 | 81.73 214 | 94.02 314 | 79.26 299 | 65.37 332 | 90.04 326 |
|
v15 | | | 86.26 280 | 84.19 283 | 92.47 273 | 93.29 273 | 93.28 202 | 98.53 255 | 95.47 309 | 82.24 302 | 74.34 318 | 87.34 324 | 81.71 215 | 94.07 312 | 79.39 298 | 65.42 330 | 90.06 325 |
|
v11 | | | 86.09 285 | 83.98 289 | 92.42 275 | 93.29 273 | 93.41 195 | 98.52 256 | 95.30 316 | 81.73 308 | 74.27 319 | 87.20 326 | 81.24 226 | 93.85 321 | 77.68 309 | 66.61 326 | 90.00 327 |
|
V9 | | | 86.16 283 | 84.07 285 | 92.43 274 | 93.27 275 | 93.04 208 | 98.40 265 | 95.45 311 | 81.98 305 | 74.18 321 | 87.31 325 | 81.58 221 | 94.06 313 | 79.12 302 | 65.33 333 | 90.20 322 |
|
v1144 | | | 91.09 227 | 89.83 232 | 94.87 211 | 93.25 276 | 93.69 186 | 99.62 151 | 96.98 261 | 86.83 261 | 89.64 222 | 94.99 263 | 80.94 229 | 97.05 253 | 85.08 266 | 81.16 267 | 93.87 268 |
|
v13 | | | 86.06 286 | 83.97 290 | 92.34 280 | 93.25 276 | 92.85 211 | 98.26 272 | 95.44 313 | 81.70 309 | 74.02 324 | 87.11 329 | 81.58 221 | 94.00 316 | 78.94 304 | 65.41 331 | 90.18 323 |
|
v12 | | | 86.10 284 | 84.01 286 | 92.37 278 | 93.23 278 | 92.96 209 | 98.33 268 | 95.45 311 | 81.87 306 | 74.05 323 | 87.15 327 | 81.60 220 | 93.98 317 | 79.09 303 | 65.28 334 | 90.18 323 |
|
v1192 | | | 90.62 238 | 89.25 243 | 94.72 217 | 93.13 279 | 93.07 205 | 99.50 165 | 97.02 255 | 86.33 267 | 89.56 225 | 95.01 260 | 79.22 249 | 97.09 252 | 82.34 284 | 81.16 267 | 94.01 248 |
|
v2v482 | | | 91.30 221 | 90.07 230 | 95.01 201 | 93.13 279 | 93.79 181 | 99.77 109 | 97.02 255 | 88.05 241 | 89.25 231 | 95.37 243 | 80.73 233 | 97.15 243 | 87.28 243 | 80.04 281 | 94.09 242 |
|
OPM-MVS | | | 93.21 185 | 92.80 181 | 94.44 227 | 93.12 281 | 90.85 255 | 99.77 109 | 97.61 201 | 96.19 41 | 91.56 190 | 98.65 152 | 75.16 282 | 98.47 169 | 93.78 158 | 89.39 212 | 93.99 254 |
|
v144192 | | | 90.79 233 | 89.52 239 | 94.59 221 | 93.11 282 | 92.77 212 | 99.56 157 | 96.99 259 | 86.38 266 | 89.82 214 | 94.95 265 | 80.50 238 | 97.10 250 | 83.98 273 | 80.41 274 | 93.90 264 |
|
PEN-MVS | | | 90.19 248 | 89.06 247 | 93.57 253 | 93.06 283 | 90.90 254 | 99.06 211 | 98.47 102 | 88.11 240 | 85.91 274 | 96.30 219 | 76.67 268 | 95.94 293 | 87.07 245 | 76.91 306 | 93.89 266 |
|
v1240 | | | 90.20 247 | 88.79 252 | 94.44 227 | 93.05 284 | 92.27 225 | 99.38 179 | 96.92 270 | 85.89 271 | 89.36 228 | 94.87 271 | 77.89 262 | 97.03 257 | 80.66 292 | 81.08 269 | 94.01 248 |
|
v148 | | | 90.70 234 | 89.63 235 | 93.92 245 | 92.97 285 | 90.97 252 | 99.75 116 | 96.89 273 | 87.51 250 | 88.27 246 | 95.01 260 | 81.67 216 | 97.04 254 | 87.40 241 | 77.17 304 | 93.75 274 |
|
v1921920 | | | 90.46 240 | 89.12 245 | 94.50 225 | 92.96 286 | 92.46 221 | 99.49 166 | 96.98 261 | 86.10 269 | 89.61 224 | 95.30 246 | 78.55 258 | 97.03 257 | 82.17 285 | 80.89 273 | 94.01 248 |
|
Baseline_NR-MVSNet | | | 90.33 243 | 89.51 240 | 92.81 265 | 92.84 287 | 89.95 269 | 99.77 109 | 93.94 331 | 84.69 286 | 89.04 235 | 95.66 232 | 81.66 217 | 96.52 275 | 90.99 193 | 76.98 305 | 91.97 304 |
|
pmmvs4 | | | 92.10 204 | 91.07 206 | 95.18 196 | 92.82 288 | 94.96 159 | 99.48 168 | 96.83 278 | 87.45 252 | 88.66 240 | 96.56 214 | 83.78 194 | 96.83 267 | 89.29 220 | 84.77 252 | 93.75 274 |
|
LF4IMVS | | | 89.25 261 | 88.85 250 | 90.45 297 | 92.81 289 | 81.19 320 | 98.12 279 | 94.79 323 | 91.44 183 | 86.29 270 | 97.11 191 | 65.30 318 | 98.11 199 | 88.53 226 | 85.25 248 | 92.07 301 |
|
pcd1.5k->3k | | | 37.58 329 | 39.62 329 | 31.46 341 | 92.73 290 | 0.00 359 | 0.00 350 | 97.52 210 | 0.00 354 | 0.00 355 | 0.00 356 | 78.40 261 | 0.00 357 | 0.00 354 | 87.90 230 | 94.37 223 |
|
DTE-MVSNet | | | 89.40 257 | 88.24 260 | 92.88 264 | 92.66 291 | 89.95 269 | 99.10 202 | 98.22 145 | 87.29 254 | 85.12 278 | 96.22 221 | 76.27 273 | 95.30 300 | 83.56 277 | 75.74 310 | 93.41 282 |
|
EU-MVSNet | | | 90.14 250 | 90.34 217 | 89.54 304 | 92.55 292 | 81.06 321 | 98.69 242 | 98.04 165 | 91.41 184 | 86.59 264 | 96.84 206 | 80.83 231 | 93.31 326 | 86.20 256 | 81.91 262 | 94.26 232 |
|
v52 | | | 89.55 255 | 88.41 257 | 92.98 261 | 92.32 293 | 90.01 267 | 98.88 228 | 96.89 273 | 84.51 287 | 86.89 259 | 94.22 285 | 79.23 248 | 97.16 241 | 84.46 269 | 78.27 292 | 91.76 306 |
|
v7n | | | 89.65 254 | 88.29 259 | 93.72 249 | 92.22 294 | 90.56 258 | 99.07 209 | 97.10 243 | 85.42 281 | 86.73 262 | 94.72 272 | 80.06 242 | 97.13 247 | 81.14 290 | 78.12 295 | 93.49 281 |
|
V4 | | | 89.55 255 | 88.41 257 | 92.98 261 | 92.21 295 | 90.03 266 | 98.87 231 | 96.91 271 | 84.51 287 | 86.84 260 | 94.21 286 | 79.37 247 | 97.15 243 | 84.45 270 | 78.28 291 | 91.76 306 |
|
PS-MVSNAJss | | | 93.64 180 | 93.31 177 | 94.61 220 | 92.11 296 | 92.19 226 | 99.12 200 | 97.38 225 | 92.51 153 | 88.45 241 | 96.99 199 | 91.20 124 | 97.29 234 | 94.36 142 | 87.71 233 | 94.36 224 |
|
pmmvs5 | | | 90.17 249 | 89.09 246 | 93.40 255 | 92.10 297 | 89.77 272 | 99.74 119 | 95.58 304 | 85.88 272 | 87.24 257 | 95.74 229 | 73.41 291 | 96.48 276 | 88.54 225 | 83.56 257 | 93.95 260 |
|
N_pmnet | | | 80.06 306 | 80.78 303 | 77.89 323 | 91.94 298 | 45.28 352 | 98.80 236 | 56.82 356 | 78.10 319 | 80.08 298 | 93.33 296 | 77.03 264 | 95.76 294 | 68.14 325 | 82.81 259 | 92.64 297 |
|
v748 | | | 88.94 264 | 87.72 265 | 92.61 269 | 91.91 299 | 87.50 290 | 99.07 209 | 96.97 264 | 84.76 284 | 85.79 275 | 93.63 295 | 79.19 250 | 97.04 254 | 83.16 279 | 75.03 314 | 93.28 286 |
|
test_djsdf | | | 92.83 191 | 92.29 190 | 94.47 226 | 91.90 300 | 92.46 221 | 99.55 159 | 97.27 232 | 91.17 192 | 89.96 207 | 96.07 226 | 81.10 227 | 96.89 263 | 94.67 137 | 88.91 215 | 94.05 245 |
|
DI_MVS_plusplus_test | | | 92.48 197 | 90.60 211 | 98.11 126 | 91.88 301 | 96.13 129 | 99.64 149 | 97.73 189 | 92.69 139 | 76.02 309 | 93.79 291 | 70.49 301 | 99.07 137 | 95.88 119 | 97.26 135 | 99.14 170 |
|
test_normal | | | 92.44 200 | 90.54 212 | 98.12 125 | 91.85 302 | 96.18 128 | 99.68 137 | 97.73 189 | 92.66 141 | 75.76 313 | 93.74 293 | 70.49 301 | 99.04 139 | 95.71 123 | 97.27 134 | 99.13 172 |
|
SixPastTwentyTwo | | | 88.73 266 | 88.01 263 | 90.88 291 | 91.85 302 | 82.24 314 | 98.22 276 | 95.18 321 | 88.97 225 | 82.26 290 | 96.89 201 | 71.75 296 | 96.67 272 | 84.00 272 | 82.98 258 | 93.72 278 |
|
K. test v3 | | | 88.05 270 | 87.24 269 | 90.47 296 | 91.82 304 | 82.23 315 | 98.96 222 | 97.42 220 | 89.05 221 | 76.93 306 | 95.60 233 | 68.49 308 | 95.42 297 | 85.87 260 | 81.01 271 | 93.75 274 |
|
OurMVSNet-221017-0 | | | 89.81 252 | 89.48 242 | 90.83 293 | 91.64 305 | 81.21 319 | 98.17 278 | 95.38 315 | 91.48 181 | 85.65 276 | 97.31 186 | 72.66 292 | 97.29 234 | 88.15 229 | 84.83 251 | 93.97 259 |
|
mvs_tets | | | 91.81 207 | 91.08 205 | 94.00 242 | 91.63 306 | 90.58 257 | 98.67 245 | 97.43 218 | 92.43 155 | 87.37 255 | 97.05 196 | 71.76 295 | 97.32 228 | 94.75 136 | 88.68 221 | 94.11 241 |
|
Gipuma | | | 66.95 317 | 65.00 316 | 72.79 328 | 91.52 307 | 67.96 332 | 66.16 348 | 95.15 322 | 47.89 342 | 58.54 338 | 67.99 345 | 29.74 347 | 87.54 338 | 50.20 343 | 77.83 297 | 62.87 348 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
jajsoiax | | | 91.92 205 | 91.18 204 | 94.15 235 | 91.35 308 | 90.95 253 | 99.00 218 | 97.42 220 | 92.61 145 | 87.38 254 | 97.08 193 | 72.46 293 | 97.36 223 | 94.53 140 | 88.77 219 | 94.13 240 |
|
MDA-MVSNet-bldmvs | | | 84.09 298 | 81.52 302 | 91.81 286 | 91.32 309 | 88.00 288 | 98.67 245 | 95.92 298 | 80.22 313 | 55.60 341 | 93.32 297 | 68.29 310 | 93.60 324 | 73.76 317 | 76.61 308 | 93.82 272 |
|
MVP-Stereo | | | 90.93 229 | 90.45 215 | 92.37 278 | 91.25 310 | 88.76 276 | 98.05 283 | 96.17 293 | 87.27 255 | 84.04 282 | 95.30 246 | 78.46 259 | 97.27 236 | 83.78 275 | 99.70 73 | 91.09 311 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
MDA-MVSNet_test_wron | | | 85.51 290 | 83.32 295 | 92.10 282 | 90.96 311 | 88.58 281 | 99.20 195 | 96.52 288 | 79.70 314 | 57.12 340 | 92.69 302 | 79.11 252 | 93.86 320 | 77.10 312 | 77.46 302 | 93.86 269 |
|
YYNet1 | | | 85.50 291 | 83.33 294 | 92.00 283 | 90.89 312 | 88.38 285 | 99.22 194 | 96.55 287 | 79.60 316 | 57.26 339 | 92.72 301 | 79.09 253 | 93.78 322 | 77.25 311 | 77.37 303 | 93.84 270 |
|
anonymousdsp | | | 91.79 211 | 90.92 207 | 94.41 230 | 90.76 313 | 92.93 210 | 98.93 225 | 97.17 239 | 89.08 220 | 87.46 253 | 95.30 246 | 78.43 260 | 96.92 262 | 92.38 174 | 88.73 220 | 93.39 284 |
|
lessismore_v0 | | | | | 90.53 294 | 90.58 314 | 80.90 322 | | 95.80 299 | | 77.01 305 | 95.84 227 | 66.15 315 | 96.95 260 | 83.03 280 | 75.05 313 | 93.74 277 |
|
EG-PatchMatch MVS | | | 85.35 292 | 83.81 293 | 89.99 302 | 90.39 315 | 81.89 317 | 98.21 277 | 96.09 295 | 81.78 307 | 74.73 314 | 93.72 294 | 51.56 339 | 97.12 249 | 79.16 301 | 88.61 222 | 90.96 313 |
|
CMPMVS | | 61.59 21 | 84.75 295 | 85.14 277 | 83.57 315 | 90.32 316 | 62.54 339 | 96.98 300 | 97.59 203 | 74.33 328 | 69.95 328 | 96.66 209 | 64.17 320 | 98.32 188 | 87.88 233 | 88.41 226 | 89.84 329 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
new_pmnet | | | 84.49 297 | 82.92 297 | 89.21 305 | 90.03 317 | 82.60 311 | 96.89 302 | 95.62 303 | 80.59 312 | 75.77 312 | 89.17 312 | 65.04 319 | 94.79 307 | 72.12 318 | 81.02 270 | 90.23 320 |
|
pmmvs6 | | | 85.69 287 | 83.84 292 | 91.26 290 | 90.00 318 | 84.41 306 | 97.82 287 | 96.15 294 | 75.86 323 | 81.29 293 | 95.39 240 | 61.21 327 | 96.87 265 | 83.52 278 | 73.29 317 | 92.50 298 |
|
DSMNet-mixed | | | 88.28 269 | 88.24 260 | 88.42 310 | 89.64 319 | 75.38 328 | 98.06 282 | 89.86 345 | 85.59 279 | 88.20 247 | 92.14 305 | 76.15 275 | 91.95 328 | 78.46 305 | 96.05 153 | 97.92 193 |
|
UnsupCasMVSNet_eth | | | 85.52 289 | 83.99 287 | 90.10 300 | 89.36 320 | 83.51 308 | 96.65 303 | 97.99 168 | 89.14 219 | 75.89 311 | 93.83 290 | 63.25 323 | 93.92 318 | 81.92 287 | 67.90 324 | 92.88 295 |
|
Anonymous20231206 | | | 86.32 279 | 85.42 275 | 89.02 306 | 89.11 321 | 80.53 324 | 99.05 214 | 95.28 317 | 85.43 280 | 82.82 288 | 93.92 288 | 74.40 286 | 93.44 325 | 66.99 327 | 81.83 263 | 93.08 291 |
|
OpenMVS_ROB | | 79.82 20 | 83.77 301 | 81.68 301 | 90.03 301 | 88.30 322 | 82.82 310 | 98.46 259 | 95.22 319 | 73.92 330 | 76.00 310 | 91.29 308 | 55.00 335 | 96.94 261 | 68.40 324 | 88.51 225 | 90.34 316 |
|
test20.03 | | | 84.72 296 | 83.99 287 | 86.91 312 | 88.19 323 | 80.62 323 | 98.88 228 | 95.94 297 | 88.36 237 | 78.87 300 | 94.62 277 | 68.75 306 | 89.11 333 | 66.52 328 | 75.82 309 | 91.00 312 |
|
Test4 | | | 88.80 265 | 85.91 274 | 97.48 144 | 87.33 324 | 95.72 142 | 99.29 189 | 97.04 254 | 92.82 130 | 70.35 327 | 91.46 307 | 44.37 342 | 97.43 220 | 93.37 164 | 97.17 139 | 99.29 152 |
|
MIMVSNet1 | | | 82.58 302 | 80.51 304 | 88.78 308 | 86.68 325 | 84.20 307 | 96.65 303 | 95.41 314 | 78.75 317 | 78.59 302 | 92.44 303 | 51.88 338 | 89.76 332 | 65.26 331 | 78.95 287 | 92.38 299 |
|
test2356 | | | 86.43 278 | 87.59 267 | 82.95 318 | 85.90 326 | 69.43 331 | 99.79 103 | 96.63 285 | 85.76 274 | 83.44 286 | 94.99 263 | 80.45 241 | 86.52 340 | 68.12 326 | 93.21 201 | 92.90 293 |
|
testus | | | 83.91 300 | 84.49 280 | 82.17 320 | 85.68 327 | 66.11 336 | 99.68 137 | 93.53 335 | 86.55 263 | 82.60 289 | 94.91 266 | 56.70 334 | 88.19 336 | 68.46 323 | 92.31 205 | 92.21 300 |
|
UnsupCasMVSNet_bld | | | 79.97 307 | 77.03 310 | 88.78 308 | 85.62 328 | 81.98 316 | 93.66 325 | 97.35 227 | 75.51 325 | 70.79 326 | 83.05 336 | 48.70 340 | 94.91 305 | 78.31 306 | 60.29 340 | 89.46 333 |
|
Patchmatch-RL test | | | 86.90 273 | 85.98 273 | 89.67 303 | 84.45 329 | 75.59 327 | 89.71 338 | 92.43 337 | 86.89 260 | 77.83 304 | 90.94 309 | 94.22 68 | 93.63 323 | 87.75 234 | 69.61 319 | 99.79 82 |
|
pmmvs-eth3d | | | 84.03 299 | 81.97 299 | 90.20 299 | 84.15 330 | 87.09 292 | 98.10 281 | 94.73 325 | 83.05 293 | 74.10 322 | 87.77 319 | 65.56 317 | 94.01 315 | 81.08 291 | 69.24 321 | 89.49 332 |
|
PM-MVS | | | 80.47 304 | 78.88 306 | 85.26 314 | 83.79 331 | 72.22 329 | 95.89 316 | 91.08 341 | 85.71 278 | 76.56 308 | 88.30 313 | 36.64 343 | 93.90 319 | 82.39 283 | 69.57 320 | 89.66 330 |
|
new-patchmatchnet | | | 81.19 303 | 79.34 305 | 86.76 313 | 82.86 332 | 80.36 325 | 97.92 285 | 95.27 318 | 82.09 304 | 72.02 325 | 86.87 330 | 62.81 324 | 90.74 331 | 71.10 319 | 63.08 336 | 89.19 334 |
|
testing_2 | | | 85.10 293 | 81.72 300 | 95.22 195 | 82.25 333 | 94.16 173 | 97.54 289 | 97.01 258 | 88.15 239 | 62.23 335 | 86.43 332 | 44.43 341 | 97.18 240 | 92.28 180 | 85.20 250 | 94.31 229 |
|
Anonymous20231211 | | | 74.17 311 | 71.17 313 | 83.17 317 | 80.58 334 | 67.02 335 | 96.27 310 | 94.45 328 | 57.31 340 | 69.60 329 | 86.25 333 | 33.67 344 | 92.96 327 | 61.86 333 | 60.50 339 | 89.54 331 |
|
pmmvs3 | | | 80.27 305 | 77.77 309 | 87.76 311 | 80.32 335 | 82.43 313 | 98.23 275 | 91.97 339 | 72.74 331 | 78.75 301 | 87.97 316 | 57.30 333 | 90.99 330 | 70.31 320 | 62.37 337 | 89.87 328 |
|
1111 | | | 79.11 308 | 78.74 307 | 80.23 321 | 78.33 336 | 67.13 333 | 97.31 293 | 93.65 333 | 71.34 332 | 68.35 331 | 87.87 317 | 85.42 185 | 88.46 334 | 52.93 341 | 73.46 316 | 85.11 337 |
|
.test1245 | | | 71.48 312 | 71.80 312 | 70.51 331 | 78.33 336 | 67.13 333 | 97.31 293 | 93.65 333 | 71.34 332 | 68.35 331 | 87.87 317 | 85.42 185 | 88.46 334 | 52.93 341 | 11.01 351 | 55.94 350 |
|
test1235678 | | | 78.45 309 | 77.88 308 | 80.16 322 | 77.83 338 | 62.18 340 | 98.36 266 | 93.45 336 | 77.46 320 | 69.08 330 | 88.23 314 | 60.33 329 | 85.41 341 | 58.46 337 | 77.68 299 | 92.90 293 |
|
ambc | | | | | 83.23 316 | 77.17 339 | 62.61 338 | 87.38 341 | 94.55 327 | | 76.72 307 | 86.65 331 | 30.16 346 | 96.36 279 | 84.85 268 | 69.86 318 | 90.73 315 |
|
TDRefinement | | | 84.76 294 | 82.56 298 | 91.38 289 | 74.58 340 | 84.80 305 | 97.36 292 | 94.56 326 | 84.73 285 | 80.21 297 | 96.12 225 | 63.56 322 | 98.39 180 | 87.92 232 | 63.97 335 | 90.95 314 |
|
test12356 | | | 75.26 310 | 75.12 311 | 75.67 327 | 74.02 341 | 60.60 342 | 96.43 306 | 92.15 338 | 74.17 329 | 66.35 333 | 88.11 315 | 52.29 337 | 84.36 343 | 57.41 338 | 75.12 312 | 82.05 338 |
|
E-PMN | | | 52.30 323 | 52.18 323 | 52.67 338 | 71.51 342 | 45.40 351 | 93.62 326 | 76.60 354 | 36.01 348 | 43.50 347 | 64.13 348 | 27.11 349 | 67.31 352 | 31.06 351 | 26.06 346 | 45.30 353 |
|
EMVS | | | 51.44 325 | 51.22 325 | 52.11 339 | 70.71 343 | 44.97 353 | 94.04 322 | 75.66 355 | 35.34 350 | 42.40 348 | 61.56 351 | 28.93 348 | 65.87 353 | 27.64 352 | 24.73 347 | 45.49 352 |
|
PMMVS2 | | | 67.15 316 | 64.15 318 | 76.14 325 | 70.56 344 | 62.07 341 | 93.89 323 | 87.52 349 | 58.09 339 | 60.02 337 | 78.32 338 | 22.38 351 | 84.54 342 | 59.56 336 | 47.03 342 | 81.80 339 |
|
no-one | | | 63.48 319 | 59.26 320 | 76.14 325 | 66.71 345 | 65.06 337 | 92.75 328 | 89.92 344 | 68.96 336 | 46.96 346 | 66.55 346 | 21.74 352 | 87.68 337 | 57.07 339 | 22.69 349 | 75.68 343 |
|
FPMVS | | | 68.72 313 | 68.72 314 | 68.71 332 | 65.95 346 | 44.27 354 | 95.97 315 | 94.74 324 | 51.13 341 | 53.26 343 | 90.50 311 | 25.11 350 | 83.00 344 | 60.80 335 | 80.97 272 | 78.87 341 |
|
PNet_i23d | | | 56.44 320 | 53.54 321 | 65.14 335 | 65.34 347 | 50.33 349 | 89.06 340 | 79.57 351 | 45.77 343 | 35.75 350 | 68.95 344 | 10.75 357 | 74.40 348 | 48.48 345 | 38.20 343 | 70.70 344 |
|
wuyk23d | | | 20.37 331 | 20.84 332 | 18.99 343 | 65.34 347 | 27.73 356 | 50.43 349 | 7.67 359 | 9.50 353 | 8.01 354 | 6.34 355 | 6.13 359 | 26.24 354 | 23.40 353 | 10.69 353 | 2.99 354 |
|
testmv | | | 67.54 315 | 65.93 315 | 72.37 329 | 64.46 349 | 54.05 346 | 95.09 319 | 90.07 343 | 68.90 337 | 55.16 342 | 77.63 340 | 30.39 345 | 82.61 345 | 49.42 344 | 62.26 338 | 80.45 340 |
|
LCM-MVSNet | | | 67.77 314 | 64.73 317 | 76.87 324 | 62.95 350 | 56.25 345 | 89.37 339 | 93.74 332 | 44.53 344 | 61.99 336 | 80.74 337 | 20.42 353 | 86.53 339 | 69.37 322 | 59.50 341 | 87.84 335 |
|
MVE | | 53.74 22 | 51.54 324 | 47.86 326 | 62.60 336 | 59.56 351 | 50.93 348 | 79.41 344 | 77.69 353 | 35.69 349 | 36.27 349 | 61.76 350 | 5.79 361 | 69.63 350 | 37.97 350 | 36.61 344 | 67.24 346 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
wuykxyi23d | | | 50.36 326 | 45.43 327 | 65.16 334 | 51.13 352 | 51.75 347 | 77.46 345 | 78.42 352 | 41.45 345 | 26.98 353 | 54.30 353 | 6.13 359 | 74.03 349 | 46.82 347 | 26.19 345 | 69.71 345 |
|
ANet_high | | | 56.10 321 | 52.24 322 | 67.66 333 | 49.27 353 | 56.82 344 | 83.94 342 | 82.02 350 | 70.47 334 | 33.28 351 | 64.54 347 | 17.23 355 | 69.16 351 | 45.59 348 | 23.85 348 | 77.02 342 |
|
tmp_tt | | | 65.23 318 | 62.94 319 | 72.13 330 | 44.90 354 | 50.03 350 | 81.05 343 | 89.42 348 | 38.45 346 | 48.51 345 | 99.90 10 | 54.09 336 | 78.70 347 | 91.84 185 | 18.26 350 | 87.64 336 |
|
PMVS | | 49.05 23 | 53.75 322 | 51.34 324 | 60.97 337 | 40.80 355 | 34.68 355 | 74.82 346 | 89.62 347 | 37.55 347 | 28.67 352 | 72.12 341 | 7.09 358 | 81.63 346 | 43.17 349 | 68.21 323 | 66.59 347 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
test123 | | | 37.68 328 | 39.14 330 | 33.31 340 | 19.94 356 | 24.83 357 | 98.36 266 | 9.75 358 | 15.53 352 | 51.31 344 | 87.14 328 | 19.62 354 | 17.74 355 | 47.10 346 | 3.47 354 | 57.36 349 |
|
testmvs | | | 40.60 327 | 44.45 328 | 29.05 342 | 19.49 357 | 14.11 358 | 99.68 137 | 18.47 357 | 20.74 351 | 64.59 334 | 98.48 164 | 10.95 356 | 17.09 356 | 56.66 340 | 11.01 351 | 55.94 350 |
|
cdsmvs_eth3d_5k | | | 23.43 330 | 31.24 331 | 0.00 344 | 0.00 358 | 0.00 359 | 0.00 350 | 98.09 161 | 0.00 354 | 0.00 355 | 99.67 75 | 83.37 197 | 0.00 357 | 0.00 354 | 0.00 355 | 0.00 355 |
|
pcd_1.5k_mvsjas | | | 7.60 333 | 10.13 334 | 0.00 344 | 0.00 358 | 0.00 359 | 0.00 350 | 0.00 360 | 0.00 354 | 0.00 355 | 0.00 356 | 91.20 124 | 0.00 357 | 0.00 354 | 0.00 355 | 0.00 355 |
|
sosnet-low-res | | | 0.00 334 | 0.00 335 | 0.00 344 | 0.00 358 | 0.00 359 | 0.00 350 | 0.00 360 | 0.00 354 | 0.00 355 | 0.00 356 | 0.00 362 | 0.00 357 | 0.00 354 | 0.00 355 | 0.00 355 |
|
sosnet | | | 0.00 334 | 0.00 335 | 0.00 344 | 0.00 358 | 0.00 359 | 0.00 350 | 0.00 360 | 0.00 354 | 0.00 355 | 0.00 356 | 0.00 362 | 0.00 357 | 0.00 354 | 0.00 355 | 0.00 355 |
|
uncertanet | | | 0.00 334 | 0.00 335 | 0.00 344 | 0.00 358 | 0.00 359 | 0.00 350 | 0.00 360 | 0.00 354 | 0.00 355 | 0.00 356 | 0.00 362 | 0.00 357 | 0.00 354 | 0.00 355 | 0.00 355 |
|
Regformer | | | 0.00 334 | 0.00 335 | 0.00 344 | 0.00 358 | 0.00 359 | 0.00 350 | 0.00 360 | 0.00 354 | 0.00 355 | 0.00 356 | 0.00 362 | 0.00 357 | 0.00 354 | 0.00 355 | 0.00 355 |
|
ab-mvs-re | | | 8.28 332 | 11.04 333 | 0.00 344 | 0.00 358 | 0.00 359 | 0.00 350 | 0.00 360 | 0.00 354 | 0.00 355 | 99.40 94 | 0.00 362 | 0.00 357 | 0.00 354 | 0.00 355 | 0.00 355 |
|
uanet | | | 0.00 334 | 0.00 335 | 0.00 344 | 0.00 358 | 0.00 359 | 0.00 350 | 0.00 360 | 0.00 354 | 0.00 355 | 0.00 356 | 0.00 362 | 0.00 357 | 0.00 354 | 0.00 355 | 0.00 355 |
|
GSMVS | | | | | | | | | | | | | | | | | 99.59 110 |
|
test_part3 | | | | | | | | 99.88 66 | | 96.14 43 | | 99.91 6 | | 100.00 1 | 99.99 1 | | |
|
test_part1 | | | | | | | | | 98.41 121 | | | | 97.20 11 | | | 99.99 13 | 99.99 11 |
|
sam_mvs1 | | | | | | | | | | | | | 94.72 55 | | | | 99.59 110 |
|
sam_mvs | | | | | | | | | | | | | 94.25 67 | | | | |
|
MTGPA | | | | | | | | | 98.28 139 | | | | | | | | |
|
test_post1 | | | | | | | | 95.78 317 | | | | 59.23 352 | 93.20 95 | 97.74 213 | 91.06 192 | | |
|
test_post | | | | | | | | | | | | 63.35 349 | 94.43 57 | 98.13 198 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 91.70 306 | 95.12 41 | 97.95 208 | | | |
|
MTMP | | | | | | | | | 96.49 289 | | | | | | | | |
|
test9_res | | | | | | | | | | | | | | | 99.71 17 | 99.99 13 | 100.00 1 |
|
agg_prior2 | | | | | | | | | | | | | | | 99.48 23 | 100.00 1 | 100.00 1 |
|
test_prior4 | | | | | | | 98.05 61 | 99.94 45 | | | | | | | | | |
|
test_prior2 | | | | | | | | 99.95 31 | | 95.78 50 | 99.73 13 | 99.76 55 | 96.00 25 | | 99.78 9 | 100.00 1 | |
|
旧先验2 | | | | | | | | 99.46 171 | | 94.21 90 | 99.85 5 | | | 99.95 50 | 96.96 106 | | |
|
新几何2 | | | | | | | | 99.40 175 | | | | | | | | | |
|
无先验 | | | | | | | | 99.49 166 | 98.71 60 | 93.46 117 | | | | 100.00 1 | 94.36 142 | | 99.99 11 |
|
原ACMM2 | | | | | | | | 99.90 59 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 99.99 27 | 90.54 201 | | |
|
segment_acmp | | | | | | | | | | | | | 96.68 14 | | | | |
|
testdata1 | | | | | | | | 99.28 190 | | 96.35 38 | | | | | | | |
|
plane_prior5 | | | | | | | | | 97.87 180 | | | | | 98.37 185 | 97.79 87 | 89.55 209 | 94.52 212 |
|
plane_prior4 | | | | | | | | | | | | 98.59 156 | | | | | |
|
plane_prior3 | | | | | | | 91.64 245 | | | 96.63 29 | 93.01 179 | | | | | | |
|
plane_prior2 | | | | | | | | 99.84 90 | | 96.38 34 | | | | | | | |
|
plane_prior | | | | | | | 91.74 239 | 99.86 86 | | 96.76 25 | | | | | | 89.59 208 | |
|
n2 | | | | | | | | | 0.00 360 | | | | | | | | |
|
nn | | | | | | | | | 0.00 360 | | | | | | | | |
|
door-mid | | | | | | | | | 89.69 346 | | | | | | | | |
|
test11 | | | | | | | | | 98.44 106 | | | | | | | | |
|
door | | | | | | | | | 90.31 342 | | | | | | | | |
|
HQP5-MVS | | | | | | | 91.85 234 | | | | | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 97.92 84 | | |
|
HQP4-MVS | | | | | | | | | | | 93.37 175 | | | 98.39 180 | | | 94.53 210 |
|
HQP3-MVS | | | | | | | | | 97.89 178 | | | | | | | 89.60 206 | |
|
HQP2-MVS | | | | | | | | | | | | | 80.65 235 | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 96.26 121 | 96.11 312 | | 91.89 171 | 98.06 95 | | 94.40 59 | | 94.30 145 | | 99.67 96 |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 87.04 238 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 88.23 228 | |
|
Test By Simon | | | | | | | | | | | | | 92.82 101 | | | | |
|